{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "1Ch3SsEFYI1u"
},
"source": [
"# **<p align=\"center\"><font size=5 color=#006600>Diplomado en Ciencia de Datos**"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "OOJ7NOMnelA2"
},
"source": [
"# **<p align=\"center\"><font size=5 color=#006600>Análisis de correspondencias múltiples (ACM)**"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "z9oBWmjodpyc"
},
"source": [
"# **<font size=5 color=#0000FF>Profesores**"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ms1l2HJYeCh7"
},
"source": [
"1. Campo Elías Pardo Turriago, cepardot@unal.edu.co \n",
"2. Alvaro Mauricio Montenegro Díaz,ammontenegrod@unal.edu.co \n",
"3. Camilo José Torres Jiménez, Msc, cjtorresj@unal.edu.co\n",
"4. Daniel Mauricio Montenegro Reyes, dextronomo@gmail.com"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "jLSx3bVoe9fZ",
"tags": []
},
"source": [
"# **<font size=5 color=#0000FF>Estudiantes auxiliares**"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "74W8jrBSfFXl"
},
"source": [
"* Jessica López Mejía, jelopezme@unal.edu.co\n",
"* Camilo Chitivo, cchitivo@unal.edu.co\n",
"* Daniel Andrés Rojas, anrojasor@unal.edu.co"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "TApWfcZxemhD"
},
"source": [
"# **<font size=5 color=#0000FF>Asesora medios y marketing digital**"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "43gtv0Abextl"
},
"source": [
"1. Maria del Pilar Montenegro, pmontenegro88@gmail.com"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "L7dnhZUdeyR7"
},
"source": [
"# Contenido"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ok00ZM5AgXw6"
},
"source": [
"* [Objetivos del ACM](#Objetivos-del-ACM)\n",
"* [Ejemplo \"de juguete\", notación y transformaciones de la tabla de datos](#Ejemplo-\"de-juguete\",-notación-y-transformaciones-de-la-tabla-de-datos)\n",
"* [El ACM como un ACS de la TDC](#El-ACM-como-un-ACS-de-la-TDC)\n",
"* [El ACM como un ACP(**X,M,N**) de la TDC](#El-ACM-como-un-ACP(X,M,N)-de-la-TDC)\n",
"* [Elementos suplementarios](#Elementos-suplementarios)\n",
"* [Ejemplo de aplicación: ACM de consumo cultural en niños de 8 a 11 años en Colombia](#Ejemplo-de-aplicación:-ACM-de-consumo-cultural-en-niños-de-8-a-11-años-en-Colombia)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Fuente: Pardo C. E. (2023). Estadística descriptiva multivariada. Universidad Nacional de Colombia Sede Bogotá. Facultad de Ciencias. \n",
"[PDF](https://drive.google.com/file/d/1ET1TOfhgUiMNyzrcEc2ZEBjKwAXb5ZJK/view?usp=drive_link)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "liXrxkeGMutK"
},
"source": [
"# **Objetivos del ACM**\n",
"\n",
"- Describir las asociaciones entre las categorías de las variables activas. \n",
"- Descubrir patrones de individuos, que pueden dar origen a grupos de ellos.\n",
"- Sintetizar en imágenes geométricas (planos factoriales) las asociaciones entre categorías y los posibles grupos de individuos.\n",
"- Explorar la explicación de la estructura inducida por las categorías activas, con variables que juegan el papel de ilustrativas.\n",
"\n",
"Adicionalmente:\n",
"\n",
"- Cuantificar las variables cualitativas. \n",
"- Reducir de dimensión.\n",
"- Filtrar: conservar la información y eliminar el ruido.\n",
"\n",
"El ACM es una extensión del ACS con propiedades muy particulares. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "tn5sP7WofAu6"
},
"source": [
"## Ejemplo \"de juguete\", notación y transformaciones de la tabla de datos\n",
"\n",
"#### Ejemplo: descripción de admitidos según algunas variables sociodemográficas, notación y transformaciones de datos\n",
"\n",
"- Descripción de los 445 admitidos a la Facultad de Ciencias, para el semestre de 2013-I.\n",
"- Datos disponibles en *admi{FactoClass}*\n",
"- Se utilizan como variables activas las sociodemográficas disponibles: \n",
" - Género: Femenino, Masculino\n",
" - Edad: 16 o menos, 17, 18, 19 o más\n",
" - Estrato: bajo, medio, alto\n",
" - Procedencia: Bogotá, Cundinamarca, Otro\n",
" \n",
"### Notación\n",
"\n",
"- La tabla de datos se denomina *de código condensado* (denotada por **Y** y no tiene significado numérico). \n",
"- Las $n$ filas representan a los individuos y \n",
"- las $s$ columnas a las variables cualitativas. \n",
"- En el lenguaje de diseño de experimentos las columnas son factores\n",
"- Las categorías son los niveles de los factores. \n",
"- En R estas variables son de tipo factor."
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "OXFwPX0aUX8t"
},
"source": [
"## Tabla de datos del ejemplo Admitidos"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 130
},
"id": "ox324ZoCutjW",
"outputId": "9eeb3b38-629b-4df1-e705-af5a0aa20a87"
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Loading required package: ade4\n",
"\n",
"Loading required package: ggplot2\n",
"\n",
"Loading required package: ggrepel\n",
"\n",
"Loading required package: xtable\n",
"\n",
"Loading required package: scatterplot3d\n",
"\n"
]
}
],
"source": [
"rm(list=ls())\n",
"library(FactoClass) # carga el paquete"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "JjZzHn6quySD"
},
"source": [
"### Tabla de datos **Y**"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"id": "eo6Efj56uE0Z",
"outputId": "290fa5b9-2a77-4c44-98dc-0383fb32bc66"
},
"outputs": [],
"source": [
"data(admi)\n",
"Y<-admi[,8:11] #tomamos las columnas genero, estrato, origen y edad"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Dimensión de Y: 445 x 4"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 17 × 4</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>gene</th><th scope=col>estr</th><th scope=col>orig</th><th scope=col>edad</th></tr>\n",
"\t<tr><th></th><th scope=col><fct></th><th scope=col><fct></th><th scope=col><fct></th><th scope=col><fct></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>25</th><td>F</td><td>medio</td><td>Otro</td><td>a17 </td></tr>\n",
"\t<tr><th scope=row>50</th><td>M</td><td>bajo </td><td>Bogo</td><td>a18 </td></tr>\n",
"\t<tr><th scope=row>75</th><td>M</td><td>bajo </td><td>Bogo</td><td>a17 </td></tr>\n",
"\t<tr><th scope=row>100</th><td>M</td><td>medio</td><td>Bogo</td><td>a18 </td></tr>\n",
"\t<tr><th scope=row>125</th><td>F</td><td>medio</td><td>Otro</td><td>a17 </td></tr>\n",
"\t<tr><th scope=row>150</th><td>F</td><td>bajo </td><td>Bogo</td><td>a16m</td></tr>\n",
"\t<tr><th scope=row>175</th><td>M</td><td>alto </td><td>Bogo</td><td>a19M</td></tr>\n",
"\t<tr><th scope=row>200</th><td>F</td><td>bajo </td><td>Otro</td><td>a17 </td></tr>\n",
"\t<tr><th scope=row>225</th><td>M</td><td>alto </td><td>Otro</td><td>a16m</td></tr>\n",
"\t<tr><th scope=row>250</th><td>M</td><td>alto </td><td>Bogo</td><td>a17 </td></tr>\n",
"\t<tr><th scope=row>275</th><td>M</td><td>bajo </td><td>Bogo</td><td>a17 </td></tr>\n",
"\t<tr><th scope=row>300</th><td>M</td><td>bajo </td><td>Otro</td><td>a19M</td></tr>\n",
"\t<tr><th scope=row>325</th><td>M</td><td>alto </td><td>Bogo</td><td>a17 </td></tr>\n",
"\t<tr><th scope=row>350</th><td>M</td><td>medio</td><td>Bogo</td><td>a19M</td></tr>\n",
"\t<tr><th scope=row>375</th><td>M</td><td>medio</td><td>Bogo</td><td>a19M</td></tr>\n",
"\t<tr><th scope=row>400</th><td>F</td><td>bajo </td><td>Bogo</td><td>a18 </td></tr>\n",
"\t<tr><th scope=row>425</th><td>M</td><td>alto </td><td>Bogo</td><td>a16m</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 17 × 4\n",
"\\begin{tabular}{r|llll}\n",
" & gene & estr & orig & edad\\\\\n",
" & <fct> & <fct> & <fct> & <fct>\\\\\n",
"\\hline\n",
"\t25 & F & medio & Otro & a17 \\\\\n",
"\t50 & M & bajo & Bogo & a18 \\\\\n",
"\t75 & M & bajo & Bogo & a17 \\\\\n",
"\t100 & M & medio & Bogo & a18 \\\\\n",
"\t125 & F & medio & Otro & a17 \\\\\n",
"\t150 & F & bajo & Bogo & a16m\\\\\n",
"\t175 & M & alto & Bogo & a19M\\\\\n",
"\t200 & F & bajo & Otro & a17 \\\\\n",
"\t225 & M & alto & Otro & a16m\\\\\n",
"\t250 & M & alto & Bogo & a17 \\\\\n",
"\t275 & M & bajo & Bogo & a17 \\\\\n",
"\t300 & M & bajo & Otro & a19M\\\\\n",
"\t325 & M & alto & Bogo & a17 \\\\\n",
"\t350 & M & medio & Bogo & a19M\\\\\n",
"\t375 & M & medio & Bogo & a19M\\\\\n",
"\t400 & F & bajo & Bogo & a18 \\\\\n",
"\t425 & M & alto & Bogo & a16m\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 17 × 4\n",
"\n",
"| <!--/--> | gene <fct> | estr <fct> | orig <fct> | edad <fct> |\n",
"|---|---|---|---|---|\n",
"| 25 | F | medio | Otro | a17 |\n",
"| 50 | M | bajo | Bogo | a18 |\n",
"| 75 | M | bajo | Bogo | a17 |\n",
"| 100 | M | medio | Bogo | a18 |\n",
"| 125 | F | medio | Otro | a17 |\n",
"| 150 | F | bajo | Bogo | a16m |\n",
"| 175 | M | alto | Bogo | a19M |\n",
"| 200 | F | bajo | Otro | a17 |\n",
"| 225 | M | alto | Otro | a16m |\n",
"| 250 | M | alto | Bogo | a17 |\n",
"| 275 | M | bajo | Bogo | a17 |\n",
"| 300 | M | bajo | Otro | a19M |\n",
"| 325 | M | alto | Bogo | a17 |\n",
"| 350 | M | medio | Bogo | a19M |\n",
"| 375 | M | medio | Bogo | a19M |\n",
"| 400 | F | bajo | Bogo | a18 |\n",
"| 425 | M | alto | Bogo | a16m |\n",
"\n"
],
"text/plain": [
" gene estr orig edad\n",
"25 F medio Otro a17 \n",
"50 M bajo Bogo a18 \n",
"75 M bajo Bogo a17 \n",
"100 M medio Bogo a18 \n",
"125 F medio Otro a17 \n",
"150 F bajo Bogo a16m\n",
"175 M alto Bogo a19M\n",
"200 F bajo Otro a17 \n",
"225 M alto Otro a16m\n",
"250 M alto Bogo a17 \n",
"275 M bajo Bogo a17 \n",
"300 M bajo Otro a19M\n",
"325 M alto Bogo a17 \n",
"350 M medio Bogo a19M\n",
"375 M medio Bogo a19M\n",
"400 F bajo Bogo a18 \n",
"425 M alto Bogo a16m"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# estracto de la tabla: múltiplo de 25\n",
"sel<-seq(25,425,25)\n",
"cat(\"\\nDimensión de Y:\",dim(Y)[1],\"x\",dim(Y)[2])\n",
"Y[sel,]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "hZrvhNXfNAWd"
},
"source": [
"### Tabla disyuntiva completa (TDC): **Z** \n",
"\n",
"La tabla **Y** no tiene sentido numérico y, por lo tanto, las cuatro particiones de los admitidos se escriben como tablas indicadoras con tantas columnas como categorías. La tabla **Z** es una contatenación de esas tablas. Su nombra se deriva de las características de las subtablas porque un partición es una unión de subconjutos disyuntos."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 189
},
"id": "gyqGaZuP8SXZ",
"outputId": "a0a5a87c-6653-46c8-d56f-035bd1b4009e"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Dimensión de Z: 445 12"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 17 × 12</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>F</th><th scope=col>M</th><th scope=col>baj</th><th scope=col>med</th><th scope=col>alt</th><th scope=col>Bog</th><th scope=col>Cun</th><th scope=col>Otr</th><th scope=col>a16</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19</th></tr>\n",
"\t<tr><th></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>25</th><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>50</th><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td></tr>\n",
"\t<tr><th scope=row>75</th><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>100</th><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td></tr>\n",
"\t<tr><th scope=row>125</th><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>150</th><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>175</th><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td></tr>\n",
"\t<tr><th scope=row>200</th><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>225</th><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>250</th><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>275</th><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>300</th><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td></tr>\n",
"\t<tr><th scope=row>325</th><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>350</th><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td></tr>\n",
"\t<tr><th scope=row>375</th><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td></tr>\n",
"\t<tr><th scope=row>400</th><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td></tr>\n",
"\t<tr><th scope=row>425</th><td>0</td><td>1</td><td>0</td><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 17 × 12\n",
"\\begin{tabular}{r|llllllllllll}\n",
" & F & M & baj & med & alt & Bog & Cun & Otr & a16 & a17 & a18 & a19\\\\\n",
" & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
"\\hline\n",
"\t25 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0\\\\\n",
"\t50 & 0 & 1 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n",
"\t75 & 0 & 1 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0\\\\\n",
"\t100 & 0 & 1 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n",
"\t125 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0\\\\\n",
"\t150 & 1 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 0\\\\\n",
"\t175 & 0 & 1 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0 & 1\\\\\n",
"\t200 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0\\\\\n",
"\t225 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 1 & 1 & 0 & 0 & 0\\\\\n",
"\t250 & 0 & 1 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 1 & 0 & 0\\\\\n",
"\t275 & 0 & 1 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0\\\\\n",
"\t300 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 1\\\\\n",
"\t325 & 0 & 1 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 1 & 0 & 0\\\\\n",
"\t350 & 0 & 1 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1\\\\\n",
"\t375 & 0 & 1 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 1\\\\\n",
"\t400 & 1 & 0 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n",
"\t425 & 0 & 1 & 0 & 0 & 1 & 1 & 0 & 0 & 1 & 0 & 0 & 0\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 17 × 12\n",
"\n",
"| <!--/--> | F <dbl> | M <dbl> | baj <dbl> | med <dbl> | alt <dbl> | Bog <dbl> | Cun <dbl> | Otr <dbl> | a16 <dbl> | a17 <dbl> | a18 <dbl> | a19 <dbl> |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| 25 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 |\n",
"| 50 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 |\n",
"| 75 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |\n",
"| 100 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 |\n",
"| 125 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 |\n",
"| 150 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 |\n",
"| 175 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 |\n",
"| 200 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 |\n",
"| 225 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |\n",
"| 250 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |\n",
"| 275 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |\n",
"| 300 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 |\n",
"| 325 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |\n",
"| 350 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 |\n",
"| 375 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 |\n",
"| 400 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 |\n",
"| 425 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 |\n",
"\n"
],
"text/plain": [
" F M baj med alt Bog Cun Otr a16 a17 a18 a19\n",
"25 1 0 0 1 0 0 0 1 0 1 0 0 \n",
"50 0 1 1 0 0 1 0 0 0 0 1 0 \n",
"75 0 1 1 0 0 1 0 0 0 1 0 0 \n",
"100 0 1 0 1 0 1 0 0 0 0 1 0 \n",
"125 1 0 0 1 0 0 0 1 0 1 0 0 \n",
"150 1 0 1 0 0 1 0 0 1 0 0 0 \n",
"175 0 1 0 0 1 1 0 0 0 0 0 1 \n",
"200 1 0 1 0 0 0 0 1 0 1 0 0 \n",
"225 0 1 0 0 1 0 0 1 1 0 0 0 \n",
"250 0 1 0 0 1 1 0 0 0 1 0 0 \n",
"275 0 1 1 0 0 1 0 0 0 1 0 0 \n",
"300 0 1 1 0 0 0 0 1 0 0 0 1 \n",
"325 0 1 0 0 1 1 0 0 0 1 0 0 \n",
"350 0 1 0 1 0 1 0 0 0 0 0 1 \n",
"375 0 1 0 1 0 1 0 0 0 0 0 1 \n",
"400 1 0 1 0 0 1 0 0 0 0 1 0 \n",
"425 0 1 0 0 1 1 0 0 1 0 0 0 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Z<-acm.disjonctif(Y) #función de ade4\n",
"cat(\"\\nDimensión de Z:\",dim(Z))\n",
"names(Z)<-substr(names(Z),6,8)\n",
"Z[sel,] #sel<-seq(25,425,25)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Extracto de 4 filas de las tablas Y y Z para ver la recodiificación"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 4 × 4</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>gene</th><th scope=col>estr</th><th scope=col>orig</th><th scope=col>edad</th></tr>\n",
"\t<tr><th></th><th scope=col><fct></th><th scope=col><fct></th><th scope=col><fct></th><th scope=col><fct></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>25</th><td>F</td><td>medio</td><td>Otro</td><td>a17</td></tr>\n",
"\t<tr><th scope=row>50</th><td>M</td><td>bajo </td><td>Bogo</td><td>a18</td></tr>\n",
"\t<tr><th scope=row>75</th><td>M</td><td>bajo </td><td>Bogo</td><td>a17</td></tr>\n",
"\t<tr><th scope=row>100</th><td>M</td><td>medio</td><td>Bogo</td><td>a18</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 4 × 4\n",
"\\begin{tabular}{r|llll}\n",
" & gene & estr & orig & edad\\\\\n",
" & <fct> & <fct> & <fct> & <fct>\\\\\n",
"\\hline\n",
"\t25 & F & medio & Otro & a17\\\\\n",
"\t50 & M & bajo & Bogo & a18\\\\\n",
"\t75 & M & bajo & Bogo & a17\\\\\n",
"\t100 & M & medio & Bogo & a18\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 4 × 4\n",
"\n",
"| <!--/--> | gene <fct> | estr <fct> | orig <fct> | edad <fct> |\n",
"|---|---|---|---|---|\n",
"| 25 | F | medio | Otro | a17 |\n",
"| 50 | M | bajo | Bogo | a18 |\n",
"| 75 | M | bajo | Bogo | a17 |\n",
"| 100 | M | medio | Bogo | a18 |\n",
"\n"
],
"text/plain": [
" gene estr orig edad\n",
"25 F medio Otro a17 \n",
"50 M bajo Bogo a18 \n",
"75 M bajo Bogo a17 \n",
"100 M medio Bogo a18 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 4 × 12</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>F</th><th scope=col>M</th><th scope=col>baj</th><th scope=col>med</th><th scope=col>alt</th><th scope=col>Bog</th><th scope=col>Cun</th><th scope=col>Otr</th><th scope=col>a16</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19</th></tr>\n",
"\t<tr><th></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>25</th><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>50</th><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td></tr>\n",
"\t<tr><th scope=row>75</th><td>0</td><td>1</td><td>1</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td></tr>\n",
"\t<tr><th scope=row>100</th><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 4 × 12\n",
"\\begin{tabular}{r|llllllllllll}\n",
" & F & M & baj & med & alt & Bog & Cun & Otr & a16 & a17 & a18 & a19\\\\\n",
" & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
"\\hline\n",
"\t25 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 1 & 0 & 0\\\\\n",
"\t50 & 0 & 1 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n",
"\t75 & 0 & 1 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 1 & 0 & 0\\\\\n",
"\t100 & 0 & 1 & 0 & 1 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & 0\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 4 × 12\n",
"\n",
"| <!--/--> | F <dbl> | M <dbl> | baj <dbl> | med <dbl> | alt <dbl> | Bog <dbl> | Cun <dbl> | Otr <dbl> | a16 <dbl> | a17 <dbl> | a18 <dbl> | a19 <dbl> |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| 25 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 |\n",
"| 50 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 |\n",
"| 75 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 |\n",
"| 100 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 |\n",
"\n"
],
"text/plain": [
" F M baj med alt Bog Cun Otr a16 a17 a18 a19\n",
"25 1 0 0 1 0 0 0 1 0 1 0 0 \n",
"50 0 1 1 0 0 1 0 0 0 0 1 0 \n",
"75 0 1 1 0 0 1 0 0 0 1 0 0 \n",
"100 0 1 0 1 0 1 0 0 0 0 1 0 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cat(\"\\nExtracto de 4 filas de las tablas Y y Z para ver la recodiificación\")\n",
"Y[sel[1:4],]\n",
"Z[sel[1:4],]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Ilcura-rqvT-"
},
"source": [
"La TDC **Z** es una yuxtaposición de *s* tablas, donde *s* es el número de variables:\n",
"\n",
"$$\\mathbf{Z}=[\\mathbf{Z}_1 \\ \\mathbf{Z}_2 \\ \\cdots \\mathbf{Z}_q \\ \\cdots \\ \\mathbf{Z}_s]$$\n",
"\n",
"- Una variable cualitativa $q$ $\\rightarrow$ Genera partición de los $n$ individuos en $p_q$ grupos, $p_q$ = número de categorías de la variable $q$ \n",
"- En cada fila de $\\mathbf{Z}_q$ siempre hay un 1 y sólo un 1. \n",
"- La suma en cada fila de $\\mathbf{Z}_q$ es de 1. \n",
"- Como hay $s$ submatrices $\\mathbf{Z}_q$, la suma de cada fila de $\\mathbf{Z}$ es $s$, es decir que su marginal fila es un vector de $n$ veces $s$ \n",
"- El total de **Z** es $ns$. \n",
"- En el ejemplo $s=4$, $n=445$ y el total de la tabla $4*445=1780$.\n",
"- La suma de cada columna de **Z** es el número de individuos que asumen la categoría $j$ que se denota $n_j$\n",
"- La $\\sum\\limits_{j \\in Z_q} n_j = n$ $\\quad Z_q$ es el conjunto de categorías de la variable $q$. \n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "zvWsYb5JNPbS"
},
"source": [
"### Tabla de Burt: $\\mathbf{B} = \\mathbf{Z^T Z}$"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"id": "0B35IaJFUX8x",
"outputId": "9a4cd993-ce0b-4933-cf2d-12458c264efa"
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 12 × 12 of type dbl</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>F</th><th scope=col>M</th><th scope=col>baj</th><th scope=col>med</th><th scope=col>alt</th><th scope=col>Bog</th><th scope=col>Cun</th><th scope=col>Otr</th><th scope=col>a16</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>F</th><td>128</td><td> 0</td><td> 46</td><td> 59</td><td>23</td><td> 89</td><td> 9</td><td>30</td><td> 46</td><td> 45</td><td>18</td><td> 19</td></tr>\n",
"\t<tr><th scope=row>M</th><td> 0</td><td>317</td><td>133</td><td>126</td><td>58</td><td>222</td><td>29</td><td>66</td><td> 72</td><td>126</td><td>38</td><td> 81</td></tr>\n",
"\t<tr><th scope=row>baj</th><td> 46</td><td>133</td><td>179</td><td> 0</td><td> 0</td><td> 95</td><td>22</td><td>62</td><td> 44</td><td> 58</td><td>22</td><td> 55</td></tr>\n",
"\t<tr><th scope=row>med</th><td> 59</td><td>126</td><td> 0</td><td>185</td><td> 0</td><td>151</td><td>11</td><td>23</td><td> 47</td><td> 74</td><td>26</td><td> 38</td></tr>\n",
"\t<tr><th scope=row>alt</th><td> 23</td><td> 58</td><td> 0</td><td> 0</td><td>81</td><td> 65</td><td> 5</td><td>11</td><td> 27</td><td> 39</td><td> 8</td><td> 7</td></tr>\n",
"\t<tr><th scope=row>Bog</th><td> 89</td><td>222</td><td> 95</td><td>151</td><td>65</td><td>311</td><td> 0</td><td> 0</td><td> 70</td><td>116</td><td>47</td><td> 78</td></tr>\n",
"\t<tr><th scope=row>Cun</th><td> 9</td><td> 29</td><td> 22</td><td> 11</td><td> 5</td><td> 0</td><td>38</td><td> 0</td><td> 9</td><td> 19</td><td> 2</td><td> 8</td></tr>\n",
"\t<tr><th scope=row>Otr</th><td> 30</td><td> 66</td><td> 62</td><td> 23</td><td>11</td><td> 0</td><td> 0</td><td>96</td><td> 39</td><td> 36</td><td> 7</td><td> 14</td></tr>\n",
"\t<tr><th scope=row>a16</th><td> 46</td><td> 72</td><td> 44</td><td> 47</td><td>27</td><td> 70</td><td> 9</td><td>39</td><td>118</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><th scope=row>a17</th><td> 45</td><td>126</td><td> 58</td><td> 74</td><td>39</td><td>116</td><td>19</td><td>36</td><td> 0</td><td>171</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><th scope=row>a18</th><td> 18</td><td> 38</td><td> 22</td><td> 26</td><td> 8</td><td> 47</td><td> 2</td><td> 7</td><td> 0</td><td> 0</td><td>56</td><td> 0</td></tr>\n",
"\t<tr><th scope=row>a19</th><td> 19</td><td> 81</td><td> 55</td><td> 38</td><td> 7</td><td> 78</td><td> 8</td><td>14</td><td> 0</td><td> 0</td><td> 0</td><td>100</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 12 × 12 of type dbl\n",
"\\begin{tabular}{r|llllllllllll}\n",
" & F & M & baj & med & alt & Bog & Cun & Otr & a16 & a17 & a18 & a19\\\\\n",
"\\hline\n",
"\tF & 128 & 0 & 46 & 59 & 23 & 89 & 9 & 30 & 46 & 45 & 18 & 19\\\\\n",
"\tM & 0 & 317 & 133 & 126 & 58 & 222 & 29 & 66 & 72 & 126 & 38 & 81\\\\\n",
"\tbaj & 46 & 133 & 179 & 0 & 0 & 95 & 22 & 62 & 44 & 58 & 22 & 55\\\\\n",
"\tmed & 59 & 126 & 0 & 185 & 0 & 151 & 11 & 23 & 47 & 74 & 26 & 38\\\\\n",
"\talt & 23 & 58 & 0 & 0 & 81 & 65 & 5 & 11 & 27 & 39 & 8 & 7\\\\\n",
"\tBog & 89 & 222 & 95 & 151 & 65 & 311 & 0 & 0 & 70 & 116 & 47 & 78\\\\\n",
"\tCun & 9 & 29 & 22 & 11 & 5 & 0 & 38 & 0 & 9 & 19 & 2 & 8\\\\\n",
"\tOtr & 30 & 66 & 62 & 23 & 11 & 0 & 0 & 96 & 39 & 36 & 7 & 14\\\\\n",
"\ta16 & 46 & 72 & 44 & 47 & 27 & 70 & 9 & 39 & 118 & 0 & 0 & 0\\\\\n",
"\ta17 & 45 & 126 & 58 & 74 & 39 & 116 & 19 & 36 & 0 & 171 & 0 & 0\\\\\n",
"\ta18 & 18 & 38 & 22 & 26 & 8 & 47 & 2 & 7 & 0 & 0 & 56 & 0\\\\\n",
"\ta19 & 19 & 81 & 55 & 38 & 7 & 78 & 8 & 14 & 0 & 0 & 0 & 100\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 12 × 12 of type dbl\n",
"\n",
"| <!--/--> | F | M | baj | med | alt | Bog | Cun | Otr | a16 | a17 | a18 | a19 |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| F | 128 | 0 | 46 | 59 | 23 | 89 | 9 | 30 | 46 | 45 | 18 | 19 |\n",
"| M | 0 | 317 | 133 | 126 | 58 | 222 | 29 | 66 | 72 | 126 | 38 | 81 |\n",
"| baj | 46 | 133 | 179 | 0 | 0 | 95 | 22 | 62 | 44 | 58 | 22 | 55 |\n",
"| med | 59 | 126 | 0 | 185 | 0 | 151 | 11 | 23 | 47 | 74 | 26 | 38 |\n",
"| alt | 23 | 58 | 0 | 0 | 81 | 65 | 5 | 11 | 27 | 39 | 8 | 7 |\n",
"| Bog | 89 | 222 | 95 | 151 | 65 | 311 | 0 | 0 | 70 | 116 | 47 | 78 |\n",
"| Cun | 9 | 29 | 22 | 11 | 5 | 0 | 38 | 0 | 9 | 19 | 2 | 8 |\n",
"| Otr | 30 | 66 | 62 | 23 | 11 | 0 | 0 | 96 | 39 | 36 | 7 | 14 |\n",
"| a16 | 46 | 72 | 44 | 47 | 27 | 70 | 9 | 39 | 118 | 0 | 0 | 0 |\n",
"| a17 | 45 | 126 | 58 | 74 | 39 | 116 | 19 | 36 | 0 | 171 | 0 | 0 |\n",
"| a18 | 18 | 38 | 22 | 26 | 8 | 47 | 2 | 7 | 0 | 0 | 56 | 0 |\n",
"| a19 | 19 | 81 | 55 | 38 | 7 | 78 | 8 | 14 | 0 | 0 | 0 | 100 |\n",
"\n"
],
"text/plain": [
" F M baj med alt Bog Cun Otr a16 a17 a18 a19\n",
"F 128 0 46 59 23 89 9 30 46 45 18 19\n",
"M 0 317 133 126 58 222 29 66 72 126 38 81\n",
"baj 46 133 179 0 0 95 22 62 44 58 22 55\n",
"med 59 126 0 185 0 151 11 23 47 74 26 38\n",
"alt 23 58 0 0 81 65 5 11 27 39 8 7\n",
"Bog 89 222 95 151 65 311 0 0 70 116 47 78\n",
"Cun 9 29 22 11 5 0 38 0 9 19 2 8\n",
"Otr 30 66 62 23 11 0 0 96 39 36 7 14\n",
"a16 46 72 44 47 27 70 9 39 118 0 0 0\n",
"a17 45 126 58 74 39 116 19 36 0 171 0 0\n",
"a18 18 38 22 26 8 47 2 7 0 0 56 0\n",
"a19 19 81 55 38 7 78 8 14 0 0 0 100"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Z<-as.matrix(Z)\n",
"B<-t(Z)%*%Z\n",
"B"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Ku0-4Z7DUX8x"
},
"source": [
"- **B** es de orden $p\\times p$\n",
"- Se denota la yuxtaposición de tablas de contingencia cruzando todas las variables por parejas, como:\n",
"$$\\mathbf{Z'}_q\\mathbf{Z}_{q'}$$\n",
"- Bloque diagonal con matrices diagonales\n",
" $$\\mathbf{Z'}_q\\mathbf{Z}_{q} = diag(n_j), \\ \\ \\ j \\in J_q$$ \n",
"- La matriz diagonal con los elementos diagonales de $\\mathbf{B}$ = suma de las columnas de **Z**:\n",
"$$\\mathbf{D}_p = diag(n_j)$$"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"id": "DjK95AXPUX8x",
"outputId": "60780046-90df-472f-e76f-2cedbdc2aff8"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Dp: matriz diagonal con elementos de la tabla de BURT (B)"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 12 × 12 of type dbl</caption>\n",
"<tbody>\n",
"\t<tr><td>128</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td>317</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td>179</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td>185</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>81</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>311</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>38</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>96</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>118</td><td> 0</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>171</td><td> 0</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>56</td><td> 0</td></tr>\n",
"\t<tr><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>100</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 12 × 12 of type dbl\n",
"\\begin{tabular}{llllllllllll}\n",
"\t 128 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t 0 & 317 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t 0 & 0 & 179 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t 0 & 0 & 0 & 185 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t 0 & 0 & 0 & 0 & 81 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t 0 & 0 & 0 & 0 & 0 & 311 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t 0 & 0 & 0 & 0 & 0 & 0 & 38 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t 0 & 0 & 0 & 0 & 0 & 0 & 0 & 96 & 0 & 0 & 0 & 0\\\\\n",
"\t 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 118 & 0 & 0 & 0\\\\\n",
"\t 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 171 & 0 & 0\\\\\n",
"\t 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 56 & 0\\\\\n",
"\t 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 100\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 12 × 12 of type dbl\n",
"\n",
"| 128 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| 0 | 317 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| 0 | 0 | 179 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| 0 | 0 | 0 | 185 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| 0 | 0 | 0 | 0 | 81 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| 0 | 0 | 0 | 0 | 0 | 311 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| 0 | 0 | 0 | 0 | 0 | 0 | 38 | 0 | 0 | 0 | 0 | 0 |\n",
"| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 96 | 0 | 0 | 0 | 0 |\n",
"| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 118 | 0 | 0 | 0 |\n",
"| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 171 | 0 | 0 |\n",
"| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 56 | 0 |\n",
"| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 100 |\n",
"\n"
],
"text/plain": [
" [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]\n",
" [1,] 128 0 0 0 0 0 0 0 0 0 0 0 \n",
" [2,] 0 317 0 0 0 0 0 0 0 0 0 0 \n",
" [3,] 0 0 179 0 0 0 0 0 0 0 0 0 \n",
" [4,] 0 0 0 185 0 0 0 0 0 0 0 0 \n",
" [5,] 0 0 0 0 81 0 0 0 0 0 0 0 \n",
" [6,] 0 0 0 0 0 311 0 0 0 0 0 0 \n",
" [7,] 0 0 0 0 0 0 38 0 0 0 0 0 \n",
" [8,] 0 0 0 0 0 0 0 96 0 0 0 0 \n",
" [9,] 0 0 0 0 0 0 0 0 118 0 0 0 \n",
"[10,] 0 0 0 0 0 0 0 0 0 171 0 0 \n",
"[11,] 0 0 0 0 0 0 0 0 0 0 56 0 \n",
"[12,] 0 0 0 0 0 0 0 0 0 0 0 100 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cat(\"\\nDp: matriz diagonal con elementos de la tabla de BURT (B)\")\n",
"Dp<-diag(diag(B))\n",
"Dp"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "4MFNYKHFUX8y"
},
"source": [
"# **El ACM como un AC de la TDC**\n",
"\n",
"Considerando que el ACM y otros análisis de correspondencias se derivan del ACS, de ahora en adelante el término análisis de correspondencias simples (ACS), se cambia por análisis de correspondencias (AC) y un AC particular se identifica por la tabla que se analisa. Con esta convinción ACM es el $AC(\\mathbf{Z})$), es decir el AC de la tabla disyuntiva completa (TDC).\n",
"\n",
"Tabla de frecuencias relativas: $$\\mathbf{F}=\\dfrac{1}{ns}\\mathbf{Z}$$\n",
"- Marginales fila: $f_{i\\cdot}=\\dfrac{1}{n}; \\forall i$ \n",
"- Marginales columna: $f_{\\cdot j}=\\dfrac{n_j}{ns}; \\forall j$\n",
"- En el ejemplo: $f_{i\\cdot}=\\dfrac{1}{445}=0.22\\%; \\forall i=1,\\cdots,445$ \n",
"- $f_{\\cdot j}~=~\\dfrac{n_j}{445*4}~=\\dfrac{n_j}{1780}; \\forall j = 1,\\cdots,12$, \n",
"- Por ejemplo $f_{\\cdot 1}~=~\\dfrac{128}{1780}=7.19\\%$.\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"id": "u2CuWWLwUX8y",
"outputId": "739273cc-f5fc-4135-b89a-828eb093e493"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Extracto de 6 columnas de la tabla F"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 6 × 13 of type dbl</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>F</th><th scope=col>M</th><th scope=col>baj</th><th scope=col>med</th><th scope=col>alt</th><th scope=col>Bog</th><th scope=col>Cun</th><th scope=col>Otr</th><th scope=col>a16</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19</th><th scope=col>Sum</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>25</th><td>0.001</td><td>0.000</td><td>0.000</td><td>0.001</td><td>0</td><td>0.000</td><td>0</td><td>0.001</td><td>0.000</td><td>0.001</td><td>0.000</td><td>0</td><td>0.002</td></tr>\n",
"\t<tr><th scope=row>50</th><td>0.000</td><td>0.001</td><td>0.001</td><td>0.000</td><td>0</td><td>0.001</td><td>0</td><td>0.000</td><td>0.000</td><td>0.000</td><td>0.001</td><td>0</td><td>0.002</td></tr>\n",
"\t<tr><th scope=row>75</th><td>0.000</td><td>0.001</td><td>0.001</td><td>0.000</td><td>0</td><td>0.001</td><td>0</td><td>0.000</td><td>0.000</td><td>0.001</td><td>0.000</td><td>0</td><td>0.002</td></tr>\n",
"\t<tr><th scope=row>100</th><td>0.000</td><td>0.001</td><td>0.000</td><td>0.001</td><td>0</td><td>0.001</td><td>0</td><td>0.000</td><td>0.000</td><td>0.000</td><td>0.001</td><td>0</td><td>0.002</td></tr>\n",
"\t<tr><th scope=row>125</th><td>0.001</td><td>0.000</td><td>0.000</td><td>0.001</td><td>0</td><td>0.000</td><td>0</td><td>0.001</td><td>0.000</td><td>0.001</td><td>0.000</td><td>0</td><td>0.002</td></tr>\n",
"\t<tr><th scope=row>150</th><td>0.001</td><td>0.000</td><td>0.001</td><td>0.000</td><td>0</td><td>0.001</td><td>0</td><td>0.000</td><td>0.001</td><td>0.000</td><td>0.000</td><td>0</td><td>0.002</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 6 × 13 of type dbl\n",
"\\begin{tabular}{r|lllllllllllll}\n",
" & F & M & baj & med & alt & Bog & Cun & Otr & a16 & a17 & a18 & a19 & Sum\\\\\n",
"\\hline\n",
"\t25 & 0.001 & 0.000 & 0.000 & 0.001 & 0 & 0.000 & 0 & 0.001 & 0.000 & 0.001 & 0.000 & 0 & 0.002\\\\\n",
"\t50 & 0.000 & 0.001 & 0.001 & 0.000 & 0 & 0.001 & 0 & 0.000 & 0.000 & 0.000 & 0.001 & 0 & 0.002\\\\\n",
"\t75 & 0.000 & 0.001 & 0.001 & 0.000 & 0 & 0.001 & 0 & 0.000 & 0.000 & 0.001 & 0.000 & 0 & 0.002\\\\\n",
"\t100 & 0.000 & 0.001 & 0.000 & 0.001 & 0 & 0.001 & 0 & 0.000 & 0.000 & 0.000 & 0.001 & 0 & 0.002\\\\\n",
"\t125 & 0.001 & 0.000 & 0.000 & 0.001 & 0 & 0.000 & 0 & 0.001 & 0.000 & 0.001 & 0.000 & 0 & 0.002\\\\\n",
"\t150 & 0.001 & 0.000 & 0.001 & 0.000 & 0 & 0.001 & 0 & 0.000 & 0.001 & 0.000 & 0.000 & 0 & 0.002\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 6 × 13 of type dbl\n",
"\n",
"| <!--/--> | F | M | baj | med | alt | Bog | Cun | Otr | a16 | a17 | a18 | a19 | Sum |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| 25 | 0.001 | 0.000 | 0.000 | 0.001 | 0 | 0.000 | 0 | 0.001 | 0.000 | 0.001 | 0.000 | 0 | 0.002 |\n",
"| 50 | 0.000 | 0.001 | 0.001 | 0.000 | 0 | 0.001 | 0 | 0.000 | 0.000 | 0.000 | 0.001 | 0 | 0.002 |\n",
"| 75 | 0.000 | 0.001 | 0.001 | 0.000 | 0 | 0.001 | 0 | 0.000 | 0.000 | 0.001 | 0.000 | 0 | 0.002 |\n",
"| 100 | 0.000 | 0.001 | 0.000 | 0.001 | 0 | 0.001 | 0 | 0.000 | 0.000 | 0.000 | 0.001 | 0 | 0.002 |\n",
"| 125 | 0.001 | 0.000 | 0.000 | 0.001 | 0 | 0.000 | 0 | 0.001 | 0.000 | 0.001 | 0.000 | 0 | 0.002 |\n",
"| 150 | 0.001 | 0.000 | 0.001 | 0.000 | 0 | 0.001 | 0 | 0.000 | 0.001 | 0.000 | 0.000 | 0 | 0.002 |\n",
"\n"
],
"text/plain": [
" F M baj med alt Bog Cun Otr a16 a17 a18 a19 Sum \n",
"25 0.001 0.000 0.000 0.001 0 0.000 0 0.001 0.000 0.001 0.000 0 0.002\n",
"50 0.000 0.001 0.001 0.000 0 0.001 0 0.000 0.000 0.000 0.001 0 0.002\n",
"75 0.000 0.001 0.001 0.000 0 0.001 0 0.000 0.000 0.001 0.000 0 0.002\n",
"100 0.000 0.001 0.000 0.001 0 0.001 0 0.000 0.000 0.000 0.001 0 0.002\n",
"125 0.001 0.000 0.000 0.001 0 0.000 0 0.001 0.000 0.001 0.000 0 0.002\n",
"150 0.001 0.000 0.001 0.000 0 0.001 0 0.000 0.001 0.000 0.000 0 0.002"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Sum col 0.072 0.178 0.101 0.104 0.046 0.175 0.021 0.054 0.066 0.096 0.031 0.056\n",
"\n",
"Marginal de cada fila 1/445: 0.00225"
]
}
],
"source": [
"n<-nrow(Y) #numero de filas\n",
"s<-ncol(Y) #numero de columnas\n",
"F<-1/n/s*Z\n",
"cat(\"\\nExtracto de 6 columnas de la tabla F\")\n",
"round(addmargins(head(F[sel,]),2),3)\n",
"cat(\"Sum col\",round(colSums(F),3))\n",
"cat(\"\\n\\nMarginal de cada fila 1/445:\",round(1/nrow(Z),5))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "AeX3QUKLUX8y"
},
"source": [
"## Nube de individuos\n",
"\n",
"Los $n$ individuos conforman la nube $N_n$ en $\\mathbb{R}^p$\n",
"\n",
"- Coordenadas: filas de la tabla $\\dfrac{1}{s}\\mathbf{Z}$:\n",
"barras de altura $1/s$ cuando el individuo asume la categoría $j$ y 0 cuando no la asume.\n",
"- Peso: $\\dfrac{1}{n}$\n",
"- Métrica: $\\mathbf{M}=ns \\mathbf{D}_p^{-1}, \\quad \\mathbf{D}_p = diag(n_j)\\qquad$,término general:\n",
"$m_j = \\dfrac{ns}{n_j}$\n",
"- En el ejemplo: un perfil fila es ${\\dfrac{1}{4} z_{ij}; j=1,\\cdots,12}$, \n",
"- con peso 0.225\\%. \n",
"- Extracto de algunos perfiles "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"id": "NpiKop7TUX8y",
"outputId": "f4133d27-320a-40e4-fa96-051fd79c14ee"
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 4 × 12 of type dbl</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>F</th><th scope=col>M</th><th scope=col>baj</th><th scope=col>med</th><th scope=col>alt</th><th scope=col>Bog</th><th scope=col>Cun</th><th scope=col>Otr</th><th scope=col>a16</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>25</th><td>0.25</td><td>0.00</td><td>0.00</td><td>0.25</td><td>0</td><td>0.00</td><td>0</td><td>0.25</td><td>0</td><td>0.25</td><td>0.00</td><td>0</td></tr>\n",
"\t<tr><th scope=row>50</th><td>0.00</td><td>0.25</td><td>0.25</td><td>0.00</td><td>0</td><td>0.25</td><td>0</td><td>0.00</td><td>0</td><td>0.00</td><td>0.25</td><td>0</td></tr>\n",
"\t<tr><th scope=row>75</th><td>0.00</td><td>0.25</td><td>0.25</td><td>0.00</td><td>0</td><td>0.25</td><td>0</td><td>0.00</td><td>0</td><td>0.25</td><td>0.00</td><td>0</td></tr>\n",
"\t<tr><th scope=row>100</th><td>0.00</td><td>0.25</td><td>0.00</td><td>0.25</td><td>0</td><td>0.25</td><td>0</td><td>0.00</td><td>0</td><td>0.00</td><td>0.25</td><td>0</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 4 × 12 of type dbl\n",
"\\begin{tabular}{r|llllllllllll}\n",
" & F & M & baj & med & alt & Bog & Cun & Otr & a16 & a17 & a18 & a19\\\\\n",
"\\hline\n",
"\t25 & 0.25 & 0.00 & 0.00 & 0.25 & 0 & 0.00 & 0 & 0.25 & 0 & 0.25 & 0.00 & 0\\\\\n",
"\t50 & 0.00 & 0.25 & 0.25 & 0.00 & 0 & 0.25 & 0 & 0.00 & 0 & 0.00 & 0.25 & 0\\\\\n",
"\t75 & 0.00 & 0.25 & 0.25 & 0.00 & 0 & 0.25 & 0 & 0.00 & 0 & 0.25 & 0.00 & 0\\\\\n",
"\t100 & 0.00 & 0.25 & 0.00 & 0.25 & 0 & 0.25 & 0 & 0.00 & 0 & 0.00 & 0.25 & 0\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 4 × 12 of type dbl\n",
"\n",
"| <!--/--> | F | M | baj | med | alt | Bog | Cun | Otr | a16 | a17 | a18 | a19 |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| 25 | 0.25 | 0.00 | 0.00 | 0.25 | 0 | 0.00 | 0 | 0.25 | 0 | 0.25 | 0.00 | 0 |\n",
"| 50 | 0.00 | 0.25 | 0.25 | 0.00 | 0 | 0.25 | 0 | 0.00 | 0 | 0.00 | 0.25 | 0 |\n",
"| 75 | 0.00 | 0.25 | 0.25 | 0.00 | 0 | 0.25 | 0 | 0.00 | 0 | 0.25 | 0.00 | 0 |\n",
"| 100 | 0.00 | 0.25 | 0.00 | 0.25 | 0 | 0.25 | 0 | 0.00 | 0 | 0.00 | 0.25 | 0 |\n",
"\n"
],
"text/plain": [
" F M baj med alt Bog Cun Otr a16 a17 a18 a19\n",
"25 0.25 0.00 0.00 0.25 0 0.00 0 0.25 0 0.25 0.00 0 \n",
"50 0.00 0.25 0.25 0.00 0 0.25 0 0.00 0 0.00 0.25 0 \n",
"75 0.00 0.25 0.25 0.00 0 0.25 0 0.00 0 0.25 0.00 0 \n",
"100 0.00 0.25 0.00 0.25 0 0.25 0 0.00 0 0.00 0.25 0 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"head(1/4*Z[sel,],4)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "vD7XNmgBUX8z"
},
"source": [
"Cada perfil fila tiene barras de altura 0.25 cuando el admitido asume la categoría.\n",
"Sigue siendo un indicador de presencia/ausencia de las categorías.\n",
"\n",
"- La métrica en este espacio de los individuos tiene término general $m_j = \\dfrac{1780}{n_j}$.\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"id": "IcR3jHBkUX8z",
"outputId": "f0d8cc03-e1e9-42bb-956d-e57f75317923"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Diagonal de la matriz de métrica\n",
"\n"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 1 × 12 of type dbl</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>F</th><th scope=col>M</th><th scope=col>baj</th><th scope=col>med</th><th scope=col>alt</th><th scope=col>Bog</th><th scope=col>Cun</th><th scope=col>Otr</th><th scope=col>a16</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>metrica</th><td>13.9</td><td>5.6</td><td>9.9</td><td>9.6</td><td>22</td><td>5.7</td><td>46.8</td><td>18.5</td><td>15.1</td><td>10.4</td><td>31.8</td><td>17.8</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 1 × 12 of type dbl\n",
"\\begin{tabular}{r|llllllllllll}\n",
" & F & M & baj & med & alt & Bog & Cun & Otr & a16 & a17 & a18 & a19\\\\\n",
"\\hline\n",
"\tmetrica & 13.9 & 5.6 & 9.9 & 9.6 & 22 & 5.7 & 46.8 & 18.5 & 15.1 & 10.4 & 31.8 & 17.8\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 1 × 12 of type dbl\n",
"\n",
"| <!--/--> | F | M | baj | med | alt | Bog | Cun | Otr | a16 | a17 | a18 | a19 |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| metrica | 13.9 | 5.6 | 9.9 | 9.6 | 22 | 5.7 | 46.8 | 18.5 | 15.1 | 10.4 | 31.8 | 17.8 |\n",
"\n"
],
"text/plain": [
" F M baj med alt Bog Cun Otr a16 a17 a18 a19 \n",
"metrica 13.9 5.6 9.9 9.6 22 5.7 46.8 18.5 15.1 10.4 31.8 17.8"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cat(\"\\nDiagonal de la matriz de métrica\\n\\n\")\n",
"nj = n*s*1/diag(Dp)\n",
"names(nj)=colnames(Z)\n",
"t(data.frame(metrica=round(nj,1)))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "0wARg_PQUX8z"
},
"source": [
"## Centro de gravedad\n",
"- La coordenada $j$ del centro de gravedad $g_p$ es $\\dfrac{1}{n}\\sum\\limits_{i=1} ^n \\dfrac{1}{s} z_{ij}=\\dfrac{n_j}{ns} $, que es la marginal columna de $\\mathbf{F}=\\dfrac{1}{ns}\\mathbf{Z}$."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 437
},
"id": "9C-Rs-1vHZZp",
"outputId": "12384ed2-ce4b-484e-977f-f0c0bf78043c"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Centro de gravedad en porcentaje\n",
"\n"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 1 × 12 of type dbl</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>F</th><th scope=col>M</th><th scope=col>baj</th><th scope=col>med</th><th scope=col>alt</th><th scope=col>Bog</th><th scope=col>Cun</th><th scope=col>Otr</th><th scope=col>a16</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>centroide</th><td>7.2</td><td>17.8</td><td>10.1</td><td>10.4</td><td>4.6</td><td>17.5</td><td>2.1</td><td>5.4</td><td>6.6</td><td>9.6</td><td>3.1</td><td>5.6</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 1 × 12 of type dbl\n",
"\\begin{tabular}{r|llllllllllll}\n",
" & F & M & baj & med & alt & Bog & Cun & Otr & a16 & a17 & a18 & a19\\\\\n",
"\\hline\n",
"\tcentroide & 7.2 & 17.8 & 10.1 & 10.4 & 4.6 & 17.5 & 2.1 & 5.4 & 6.6 & 9.6 & 3.1 & 5.6\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 1 × 12 of type dbl\n",
"\n",
"| <!--/--> | F | M | baj | med | alt | Bog | Cun | Otr | a16 | a17 | a18 | a19 |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| centroide | 7.2 | 17.8 | 10.1 | 10.4 | 4.6 | 17.5 | 2.1 | 5.4 | 6.6 | 9.6 | 3.1 | 5.6 |\n",
"\n"
],
"text/plain": [
" F M baj med alt Bog Cun Otr a16 a17 a18 a19\n",
"centroide 7.2 17.8 10.1 10.4 4.6 17.5 2.1 5.4 6.6 9.6 3.1 5.6"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"cat(\"\\nCentro de gravedad en porcentaje\\n\\n\")\n",
"t(round(data.frame(centroide=colSums(1/n/s*Z)*100),1))"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "uUca4IvgUX8z"
},
"source": [
"## Distancia entre individuos \n",
"$$\n",
"d^2(i,l)=ns\\sum_{j=1}^p \\frac{1}{n_j} \\left(\\dfrac{1}{s}\\left[ z_{ij}-z_{lj} \\right] \\right)^2=\n",
"\\frac{n}{s} \\sum_{j=1}^p \\frac{1}{n_j} \\left(z_{ij}-z_{lj} \\right)^2 \n",
"$$\n",
"\n",
"- Si dos individuos se parecen = asumen más o menos las mismas categorías. \n",
"- La distancia se amplifica más cuando uno solo de los dos individuos asume una categoría de baja frecuencia.\n",
"- Por ejemplo la distancia al cuadrado entre los individuos 50 y 100 es $d^2(i50,i100)= \\dfrac{445}{4}\\left(\\dfrac{1}{179}+\\dfrac{1}{185}\\right)=1.22$ y la diferencia entre ellos en estrato bajo y medio:\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"id": "txF5ARsyUX80",
"outputId": "b57bb122-7037-4602-ea21-52b5fb3922b3"
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 2 × 4</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>gene</th><th scope=col>estr</th><th scope=col>orig</th><th scope=col>edad</th></tr>\n",
"\t<tr><th></th><th scope=col><fct></th><th scope=col><fct></th><th scope=col><fct></th><th scope=col><fct></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>50</th><td>M</td><td>bajo </td><td>Bogo</td><td>a18</td></tr>\n",
"\t<tr><th scope=row>100</th><td>M</td><td>medio</td><td>Bogo</td><td>a18</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 2 × 4\n",
"\\begin{tabular}{r|llll}\n",
" & gene & estr & orig & edad\\\\\n",
" & <fct> & <fct> & <fct> & <fct>\\\\\n",
"\\hline\n",
"\t50 & M & bajo & Bogo & a18\\\\\n",
"\t100 & M & medio & Bogo & a18\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 2 × 4\n",
"\n",
"| <!--/--> | gene <fct> | estr <fct> | orig <fct> | edad <fct> |\n",
"|---|---|---|---|---|\n",
"| 50 | M | bajo | Bogo | a18 |\n",
"| 100 | M | medio | Bogo | a18 |\n",
"\n"
],
"text/plain": [
" gene estr orig edad\n",
"50 M bajo Bogo a18 \n",
"100 M medio Bogo a18 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Y[c(50,100),]"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "mUnkvhieUX80"
},
"source": [
"## Inercia de la nube de perfiles fila\n",
"\n",
"$$\n",
"\\dfrac{1}{n} \\sum\\limits_{i=1}^n d^2(i,\\mathbf{g}_p) = \n",
"\\dfrac{1}{n} \\sum\\limits_{i=1}^n \\sum\\limits_{j=1}^p \\dfrac{ns}{n_j}(\\dfrac{z_{ij}}{s}-\\dfrac{n_j}{ns})^2= \n",
"\\dfrac{1}{s} \\sum\\limits_{j=1}^p \\dfrac{1}{n_j} \\sum\\limits_{i=1}^n (z_{ij}^2 -2 z_{ij} \\dfrac{n_j}{n} + \\dfrac{n_j^2}{n^2}) =\n",
"$$\n",
"$$\n",
"\\dfrac{1}{s} (p - 2 s + s) = \\dfrac{p}{s} - 1\n",
"$$\n",
"\n",
"- La inercia de la nube de puntos depende del cociente entre el número de categorías y el número de variables, no de los valores internos de la tabla, por lo tanto no tiene significado estadístico.\n",
"- En el ejemplo es $12/4 -1 = 2$.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "VWPPMG2TUX80",
"tags": []
},
"source": [
"## Ejes y subespacios vectoriales\n",
"\n",
"$$ \n",
"AC(Z) = ACP\\left(\\dfrac{1}{s}\\mathbf{Z},ns\\mathbf{D}_p^{-1},\\dfrac{1}{n}\\mathbf{I}_n\\right)\n",
"$$\n",
"\n",
"- La matriz de inercia es: \n",
"$$\n",
"\\dfrac{1}{s}\\mathbf{Z'}\\dfrac{1}{n}\\mathbf{I}_n\\dfrac{1}{s}\\mathbf{Z}ns\\mathbf{D}_p^{-1}=\n",
"\\dfrac{1}{s}\\mathbf{Z'Z}\\mathbf{D}_p^{-1}=\n",
"\\dfrac{1}{s}\\mathbf{B}\\mathbf{D}_p^{-1}\n",
"$$\n",
"\n",
"- El rango de esta matriz es igual al rango de **Z**, que es $p-s$, porque por cada variable hay una columna que es linealmente dependiente, \n",
"- Una columna se puede obtener como la diferencia entre el vector de $n$ unos y la suma de las demás columnas asociadas a la variable. \n",
"- La nube de puntos está soportada en un subespacio de dimensión $p-s$, que es el número de valores propios mayores que cero. \n",
"- En el ejemplo hay $12-4=8$ valores propios mayores que cero,"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "treOhm8LIQMk",
"outputId": "e4dcc81d-4051-47fd-d1c8-a80ffaac160f"
},
"source": [
"## Valores propios del ACM de admitidos"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"id": "FAtWgnurUX81",
"outputId": "bf9a0b4d-29e5-4514-a5e6-e2cdbaa73d1a"
},
"outputs": [
{
"data": {
"text/plain": [
"Inertia information:\n",
"Call: inertia.dudi(x = acm)\n",
"\n",
"Decomposition of total inertia:\n",
" inertia cum cum(%)\n",
"Ax1 0.3366 0.3366 16.83\n",
"Ax2 0.3128 0.6493 32.47\n",
"Ax3 0.2827 0.9320 46.60\n",
"Ax4 0.2471 1.1791 58.96\n",
"Ax5 0.2408 1.4199 71.00\n",
"Ax6 0.2293 1.6493 82.46\n",
"Ax7 0.2075 1.8568 92.84\n",
"Ax8 0.1432 2.0000 100.00"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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7ddq19MLkgOro20Z9y3eED/fErv0euy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",
"text/plain": [
"Plot with title “Barplot eigen-values”"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"acm<-dudi.acm(Y,scannf=FALSE,nf=3)\n",
"inertia(acm)\n",
"barplot(acm$eig,main=\"Barplot eigen-values\")\n",
"abline(h=sum(acm$eig)/8,col=\"darkgreen\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "UUZvUsG6UX81"
},
"source": [
"## Primer plano factorial del ACM de admitidos"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"id": "7Po9nJlXUX82",
"outputId": "9fd8be6c-897d-41ee-8104-a08f8d84d42e"
},
"outputs": [
{
"data": {
"image/png": 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v3jx9TEIgn8BLL71k9erVs8GDB+f7jAUIIIBAGAQIkMJwFikDAgjk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hqcOTxAtAb7v//ve/XY+Seq2uX9WotzBJo7cH9TCpH5ygQL969eq+bT4KOu/e8eji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\n77332lFHHWWnnHKKjRw5Mk8PgD/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"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plot(acm,Tcol=FALSE,gg=TRUE,roweti=sel,main=\"Primer plano factorial del ACM\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "musNzONJUX82"
},
"source": [
"# Nube de categorías\n",
"\n",
"### Coordenadas: Columnas de la tabla $\\mathbf{ZD}^{-1}_p$\n",
"\n",
"- Cada perfil columna $j$ tiene solo dos alturas: cero o $1/n_j$. \n",
"- Las alturas son en general, diferentes en cada perfil. \n",
"- El peso de cada categoría es $\\dfrac{n_j}{ns}$\n",
"\n",
"### Centro de gravedad: Es el vector de $n$ valores $\\dfrac{1}{n}$\n",
"\n",
"- Coordenada $i$ del centro de gravedad: \n",
"$$ \\mathbf{g}(i) = \\sum_{j=1}^p \\frac{n_j}{ns} \\frac{z_{ij}}{n_j} =\n",
" \\sum_{j=1}^p \\frac{1}{ns} z_{ij} = \\frac{1}{ns} s = \\frac{1}{n}\n",
" $$\n",
"\n",
"### Métrica: $n \\mathbf{I}_n$\n",
"\n",
"### Distancia entre dos categorías\n",
"\n",
"$$\n",
"d^2(j,k) = \\sum_{i=1}^n n \\left(\\frac{z_{ij}}{n_j} - \\frac{z_{ik}}{n_k}\\right)^2\n",
"$$"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "Czv7vEx1UX82"
},
"source": [
"**Interpretación de la distancia entre categorías**\n",
"\n",
"\n",
" Categoría k \n",
" \n",
" | 1 | 0 | suma\n",
" -------------------- \n",
" Categoria 1 | a | b | n_j\n",
"\n",
" j 0 | c | d | c+d\n",
" -------------------- \n",
" suma | n_k | b+d | n\n",
" \n",
"$$\n",
"d^2(j,k) = n \\left( \\frac{n_k + n_j - 2a}{n_j n_k} \\right) = \n",
"n \\left( \\frac{a+c+a+b - 2a}{n_j n_k} \\right) = \\frac{n}{n_j n_k} (b+c)\n",
"$$ \n",
"\n",
"- En la distancia de dos categorías, sólo se suman los individuos que asumen una y solo una de las dos categorías. \n",
"- Las categorías de baja frecuencia se alejan más de las demás.\n",
"\n",
"### Contribución de categorías y variables a la inercia \n",
"\n",
"- Distancia entre la categoría $j$ y el centro de gravedad $\\mathbf{g}_n=\\dfrac{1}{n}\\mathbf{1}_n$:\n",
"\n",
"$$\n",
"d^2(j,\\mathbf{g}_n) = n \\sum_{i=1}^{n} \\left( \\frac{z_{ij}}{n_j} - \\frac{1}{n} \\right)^2 =\n",
"n \\sum_{i=1}^n \\left(\\frac{z_{ij}^2}{n_j^2}-2 \\frac{z_{ij}}{n_j} \\frac{1}{n} + \\frac{1}{n^2}\\right)=\n",
" \\frac{n}{n_j} - 1\n",
"$$\n",
"\n",
"- Las categorías de menos frecuencia son las más alejadas del origen\n",
"\n",
"$$\n",
"I(N_p) =\\sum_{q=1}^s \\sum_{j \\in J_q} \\frac{n_j}{ns} d^2(j,\\mathbf{g}_n) = \n",
"\\sum_{q=1}^s \\sum_{j \\in J_q} \\frac{n_j}{ns} \\left(\\frac{n}{n_j}-1\\right) =\n",
"\\sum_{q=1}^s \\sum_{j \\in J_q} \\frac{1}{s} \\left(1-\\frac{n_j}{n}\\right) \n",
"$$\n",
"\n",
"- $J_q$ es el conjunto de categorías que pertenecen la variable $q$. \n",
"\n",
"\n",
"**Contribuciones a la inercia**\n",
"\n",
"- De una categoría $j$: $ \\dfrac{1}{s}\\left(1-\\dfrac{n_j}{n}\\right) $, contribuyen más las categorías de baja frecuencia.\n",
"- De una variable $q$: $\\sum\\limits_{j \\in J_q} \\dfrac{1}{s} \\left(1-\\dfrac{n_j}{n}\\right) = \n",
"\\dfrac{1}{s}\\left(p_q-\\dfrac{n}{n}\\right) = \\dfrac{1}{s}\\left(p_q-1\\right)$, contribuyen más las variables con más categorías\n",
"- Inercia total: $\\sum\\limits_{q=1}^s \\dfrac{1}{s}\\left(p_q-1\\right) = \\dfrac{1}{s}(p-s) =\\dfrac{p}{s}-1$. No tiene significado estadístico, no depende de los valores de la tabla sino de la relación entre número de categorías y número de variables.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "KGHBZaGTUX82"
},
"source": [
"## Subespacio de proyección de las categorías\n",
"\n",
"### Primer plano factorial"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"id": "-Q9zBDkyUX83",
"outputId": "52073ef9-408a-494f-be49-db8e4cdea3a7"
},
"outputs": [
{
"data": {
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wH5egYKscbbBeGOtRsWK9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\nar7Vvwnz+sUvv/zSj4866ig3KH/55ZdCT0bUQ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CANjufMXUIAAhCAwCAnYEUSfNHfVDXu/x2HSpIrpE5l2LVuGAIBCECgUwIYSJ2SQg8C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\nCEAAAhCAAAQgAIHmEvgPjTfj62hVenAAAAAASUVORK5CYII=",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plot(acm,Trow=FALSE,gg=TRUE,main=\"Factores 1-2\")"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "I--pRANzJW-D"
},
"source": [
"### Coordenadas y ayudas para la interpretación de las categorías para los tres primeros ejes"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"id": "BRzuRUrNUX83",
"outputId": "dbe229de-d06b-4f4b-dded-816ea9b6dc3b"
},
"outputs": [
{
"data": {
"text/html": [
"<style>\n",
".list-inline {list-style: none; margin:0; padding: 0}\n",
".list-inline>li {display: inline-block}\n",
".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
"</style>\n",
"<ol class=list-inline><li>'tot.inertia'</li><li>'col.contrib'</li><li>'col.abs'</li><li>'col.rel'</li><li>'col.cum'</li><li>'nf'</li><li>'call'</li></ol>\n"
],
"text/latex": [
"\\begin{enumerate*}\n",
"\\item 'tot.inertia'\n",
"\\item 'col.contrib'\n",
"\\item 'col.abs'\n",
"\\item 'col.rel'\n",
"\\item 'col.cum'\n",
"\\item 'nf'\n",
"\\item 'call'\n",
"\\end{enumerate*}\n"
],
"text/markdown": [
"1. 'tot.inertia'\n",
"2. 'col.contrib'\n",
"3. 'col.abs'\n",
"4. 'col.rel'\n",
"5. 'col.cum'\n",
"6. 'nf'\n",
"7. 'call'\n",
"\n",
"\n"
],
"text/plain": [
"[1] \"tot.inertia\" \"col.contrib\" \"col.abs\" \"col.rel\" \"col.cum\" \n",
"[6] \"nf\" \"call\" "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 12 × 10</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>Comp1</th><th scope=col>Comp2</th><th scope=col>Comp3</th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Axis3</th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Axis3</th><th scope=col>ayuacm$col.contrib</th></tr>\n",
"\t<tr><th></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>gene.F</th><td> 0.13</td><td> 0.89</td><td>-0.51</td><td> 0.36</td><td>18.21</td><td> 6.66</td><td> 0.67</td><td> 31.97</td><td>-10.58</td><td> 8.90</td></tr>\n",
"\t<tr><th scope=row>gene.M</th><td>-0.05</td><td>-0.36</td><td> 0.21</td><td> 0.14</td><td> 7.35</td><td> 2.69</td><td> -0.67</td><td>-31.97</td><td> 10.58</td><td> 3.60</td></tr>\n",
"\t<tr><th scope=row>estr.bajo</th><td>-0.93</td><td>-0.31</td><td>-0.18</td><td>25.90</td><td> 3.15</td><td> 1.17</td><td>-58.34</td><td> -6.58</td><td> -2.21</td><td> 7.47</td></tr>\n",
"\t<tr><th scope=row>estr.medio</th><td> 0.67</td><td>-0.04</td><td>-0.31</td><td>13.71</td><td> 0.05</td><td> 3.61</td><td> 31.59</td><td> -0.10</td><td> -6.99</td><td> 7.30</td></tr>\n",
"\t<tr><th scope=row>estr.alto</th><td> 0.54</td><td> 0.78</td><td> 1.12</td><td> 3.88</td><td> 8.75</td><td>20.06</td><td> 6.39</td><td> 13.38</td><td> 27.73</td><td>10.22</td></tr>\n",
"\t<tr><th scope=row>orig.Bogo</th><td> 0.51</td><td>-0.13</td><td>-0.11</td><td>13.45</td><td> 0.91</td><td> 0.70</td><td> 60.15</td><td> -3.76</td><td> -2.65</td><td> 3.76</td></tr>\n",
"\t<tr><th scope=row>orig.Cund</th><td>-0.88</td><td>-0.61</td><td> 1.44</td><td> 4.87</td><td> 2.51</td><td>15.72</td><td> -7.16</td><td> -3.44</td><td> 19.43</td><td>11.43</td></tr>\n",
"\t<tr><th scope=row>orig.Otro</th><td>-1.30</td><td> 0.65</td><td>-0.23</td><td>27.18</td><td> 7.34</td><td> 0.97</td><td>-46.66</td><td> 11.71</td><td> -1.39</td><td> 9.80</td></tr>\n",
"\t<tr><th scope=row>edad.a16m</th><td>-0.39</td><td> 1.07</td><td>-0.29</td><td> 3.04</td><td>24.09</td><td> 1.99</td><td> -5.56</td><td> 41.02</td><td> -3.07</td><td> 9.19</td></tr>\n",
"\t<tr><th scope=row>edad.a17</th><td> 0.19</td><td> 0.03</td><td> 0.88</td><td> 0.98</td><td> 0.03</td><td>26.54</td><td> 2.14</td><td> 0.06</td><td> 48.74</td><td> 7.70</td></tr>\n",
"\t<tr><th scope=row>edad.a18</th><td> 0.75</td><td>-0.14</td><td>-1.13</td><td> 5.24</td><td> 0.18</td><td>14.21</td><td> 8.08</td><td> -0.26</td><td>-18.38</td><td>10.93</td></tr>\n",
"\t<tr><th scope=row>edad.a19M</th><td>-0.27</td><td>-1.24</td><td>-0.53</td><td> 1.24</td><td>27.43</td><td> 5.67</td><td> -2.16</td><td>-44.26</td><td> -8.27</td><td> 9.69</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 12 × 10\n",
"\\begin{tabular}{r|llllllllll}\n",
" & Comp1 & Comp2 & Comp3 & Axis1 & Axis2 & Axis3 & Axis1 & Axis2 & Axis3 & ayuacm\\$col.contrib\\\\\n",
" & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
"\\hline\n",
"\tgene.F & 0.13 & 0.89 & -0.51 & 0.36 & 18.21 & 6.66 & 0.67 & 31.97 & -10.58 & 8.90\\\\\n",
"\tgene.M & -0.05 & -0.36 & 0.21 & 0.14 & 7.35 & 2.69 & -0.67 & -31.97 & 10.58 & 3.60\\\\\n",
"\testr.bajo & -0.93 & -0.31 & -0.18 & 25.90 & 3.15 & 1.17 & -58.34 & -6.58 & -2.21 & 7.47\\\\\n",
"\testr.medio & 0.67 & -0.04 & -0.31 & 13.71 & 0.05 & 3.61 & 31.59 & -0.10 & -6.99 & 7.30\\\\\n",
"\testr.alto & 0.54 & 0.78 & 1.12 & 3.88 & 8.75 & 20.06 & 6.39 & 13.38 & 27.73 & 10.22\\\\\n",
"\torig.Bogo & 0.51 & -0.13 & -0.11 & 13.45 & 0.91 & 0.70 & 60.15 & -3.76 & -2.65 & 3.76\\\\\n",
"\torig.Cund & -0.88 & -0.61 & 1.44 & 4.87 & 2.51 & 15.72 & -7.16 & -3.44 & 19.43 & 11.43\\\\\n",
"\torig.Otro & -1.30 & 0.65 & -0.23 & 27.18 & 7.34 & 0.97 & -46.66 & 11.71 & -1.39 & 9.80\\\\\n",
"\tedad.a16m & -0.39 & 1.07 & -0.29 & 3.04 & 24.09 & 1.99 & -5.56 & 41.02 & -3.07 & 9.19\\\\\n",
"\tedad.a17 & 0.19 & 0.03 & 0.88 & 0.98 & 0.03 & 26.54 & 2.14 & 0.06 & 48.74 & 7.70\\\\\n",
"\tedad.a18 & 0.75 & -0.14 & -1.13 & 5.24 & 0.18 & 14.21 & 8.08 & -0.26 & -18.38 & 10.93\\\\\n",
"\tedad.a19M & -0.27 & -1.24 & -0.53 & 1.24 & 27.43 & 5.67 & -2.16 & -44.26 & -8.27 & 9.69\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 12 × 10\n",
"\n",
"| <!--/--> | Comp1 <dbl> | Comp2 <dbl> | Comp3 <dbl> | Axis1 <dbl> | Axis2 <dbl> | Axis3 <dbl> | Axis1 <dbl> | Axis2 <dbl> | Axis3 <dbl> | ayuacm$col.contrib <dbl> |\n",
"|---|---|---|---|---|---|---|---|---|---|---|\n",
"| gene.F | 0.13 | 0.89 | -0.51 | 0.36 | 18.21 | 6.66 | 0.67 | 31.97 | -10.58 | 8.90 |\n",
"| gene.M | -0.05 | -0.36 | 0.21 | 0.14 | 7.35 | 2.69 | -0.67 | -31.97 | 10.58 | 3.60 |\n",
"| estr.bajo | -0.93 | -0.31 | -0.18 | 25.90 | 3.15 | 1.17 | -58.34 | -6.58 | -2.21 | 7.47 |\n",
"| estr.medio | 0.67 | -0.04 | -0.31 | 13.71 | 0.05 | 3.61 | 31.59 | -0.10 | -6.99 | 7.30 |\n",
"| estr.alto | 0.54 | 0.78 | 1.12 | 3.88 | 8.75 | 20.06 | 6.39 | 13.38 | 27.73 | 10.22 |\n",
"| orig.Bogo | 0.51 | -0.13 | -0.11 | 13.45 | 0.91 | 0.70 | 60.15 | -3.76 | -2.65 | 3.76 |\n",
"| orig.Cund | -0.88 | -0.61 | 1.44 | 4.87 | 2.51 | 15.72 | -7.16 | -3.44 | 19.43 | 11.43 |\n",
"| orig.Otro | -1.30 | 0.65 | -0.23 | 27.18 | 7.34 | 0.97 | -46.66 | 11.71 | -1.39 | 9.80 |\n",
"| edad.a16m | -0.39 | 1.07 | -0.29 | 3.04 | 24.09 | 1.99 | -5.56 | 41.02 | -3.07 | 9.19 |\n",
"| edad.a17 | 0.19 | 0.03 | 0.88 | 0.98 | 0.03 | 26.54 | 2.14 | 0.06 | 48.74 | 7.70 |\n",
"| edad.a18 | 0.75 | -0.14 | -1.13 | 5.24 | 0.18 | 14.21 | 8.08 | -0.26 | -18.38 | 10.93 |\n",
"| edad.a19M | -0.27 | -1.24 | -0.53 | 1.24 | 27.43 | 5.67 | -2.16 | -44.26 | -8.27 | 9.69 |\n",
"\n"
],
"text/plain": [
" Comp1 Comp2 Comp3 Axis1 Axis2 Axis3 Axis1 Axis2 Axis3 \n",
"gene.F 0.13 0.89 -0.51 0.36 18.21 6.66 0.67 31.97 -10.58\n",
"gene.M -0.05 -0.36 0.21 0.14 7.35 2.69 -0.67 -31.97 10.58\n",
"estr.bajo -0.93 -0.31 -0.18 25.90 3.15 1.17 -58.34 -6.58 -2.21\n",
"estr.medio 0.67 -0.04 -0.31 13.71 0.05 3.61 31.59 -0.10 -6.99\n",
"estr.alto 0.54 0.78 1.12 3.88 8.75 20.06 6.39 13.38 27.73\n",
"orig.Bogo 0.51 -0.13 -0.11 13.45 0.91 0.70 60.15 -3.76 -2.65\n",
"orig.Cund -0.88 -0.61 1.44 4.87 2.51 15.72 -7.16 -3.44 19.43\n",
"orig.Otro -1.30 0.65 -0.23 27.18 7.34 0.97 -46.66 11.71 -1.39\n",
"edad.a16m -0.39 1.07 -0.29 3.04 24.09 1.99 -5.56 41.02 -3.07\n",
"edad.a17 0.19 0.03 0.88 0.98 0.03 26.54 2.14 0.06 48.74\n",
"edad.a18 0.75 -0.14 -1.13 5.24 0.18 14.21 8.08 -0.26 -18.38\n",
"edad.a19M -0.27 -1.24 -0.53 1.24 27.43 5.67 -2.16 -44.26 -8.27\n",
" ayuacm$col.contrib\n",
"gene.F 8.90 \n",
"gene.M 3.60 \n",
"estr.bajo 7.47 \n",
"estr.medio 7.30 \n",
"estr.alto 10.22 \n",
"orig.Bogo 3.76 \n",
"orig.Cund 11.43 \n",
"orig.Otro 9.80 \n",
"edad.a16m 9.19 \n",
"edad.a17 7.70 \n",
"edad.a18 10.93 \n",
"edad.a19M 9.69 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"16.67"
],
"text/latex": [
"16.67"
],
"text/markdown": [
"16.67"
],
"text/plain": [
"[1] 16.67"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ayuacm<-inertia(acm,,T)\n",
"names(ayuacm)\n",
"round(cbind(acm$co,ayuacm$col.abs,ayuacm$col.rel,ayuacm$col.contrib),2)\n",
"round(sum(acm$eig)/12*100,2)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "i6hhWVEQUX83",
"tags": []
},
"source": [
"# **El ACM como un ACP(X,M,N) de la TDC)**\n",
"\n",
" $$\n",
" ACP(\\mathbf{X,M,N})\n",
" $$\n",
"\n",
"- $\\mathbf{X}= n \\mathbf{I}_n\\dfrac{1}{ns}\\mathbf{Z} ns \\mathbf{D}=n\\mathbf{ZD}_p^{-1}$, \n",
" - término general: $x_{ij}=\\dfrac{n}{n_j} z_{ij}$.\n",
"- $\\mathbf{M}=\\dfrac{1}{ns}\\mathbf{D}_p$, \n",
" - término general: $m_j = \\dfrac{n_j}{ns}$.\n",
"- $\\mathbf{N}=\\dfrac{1}{n}\\mathbf{I}_n$, \n",
" - término general: $d_i=\\dfrac{1}{n}$.\n",
"\n",
"#### **M** - distancia al cuadrado entre dos individuos $i$ y $l$ \n",
"$$\n",
"d^2(i,l) = \\sum_{j=1}^p \\dfrac{n_j}{ns} \\left(\\dfrac{n}{n_j} z_{ij}-\\dfrac{n}{n_j} z_{lj} \\right)^2 \n",
" = \\dfrac{n}{s} \\sum_{j=1}^p \\dfrac{1}{n_j} (z_{ij} - z_{lj})^2\n",
"$$\n",
"#### **N** - distancia al cuadrado entre dos categorías\n",
"$j$ y $k$ de **X**\n",
"$$\n",
"d^2(j,k)= \\sum_{i=1}^n \\frac{1}{n}\\left(\\dfrac{n}{n_j} z_{ij}-\\dfrac{n}{n_k} z_{ik} \\right)^2\n",
" = n \\sum_{i=1}^n \\left(\\dfrac{z_{ij}}{n_j} -\\dfrac{z_{ik}}{n_k} \\right)^2\n",
"$$\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "7grG9ZYcUX84"
},
"source": [
"## Relaciones cuasibaricéntricas\n",
"\n",
"#### Coordenada de un individuo en función de las coordenadas de las categorías\n",
"\n",
"\n",
"$$\n",
" F_s(i) = \\frac{1}{\\sqrt{\\lambda_s}} \\frac{1}{s} \\sum_{j=1}^p z_{ij} G_s(j) \n",
" = \\frac{1}{\\sqrt{\\lambda_s}} \\frac{1}{s} \\sum_{j \\in J_i} G_s(j)\n",
"$$\n",
"\n",
"\n",
"- $J_i$ es el conjunto de categorías que son asumidas por el individuo $i$.\n",
"- La coordenada sobre un eje $s$ del individuo $i$ se sitúa en el promedio aritmético de las coordenadas de las categorías que asume, dilatadas por el inverso de la raíz cuadrada del valor propio. \n",
"\n",
"- Ejemplo: el primer individuo de la tabla asume las categorías:\n",
"\n",
" - Ge.F (0.1) es la coordenada sobre el primer eje, Ed.17 (0.2), Es.medio (0.7) y - Or.Otro (-1.3). \n",
" - Promedio aritmético: (0.1+0.2+0.7-1.3)/4 = -0.08. \n",
" - La dilatación es $1/\\sqrt{0.337}=1.72$.\n",
" - La coordenada es 1.72*(~-0.08) = -0.14. \n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "_-FB0qtqUX84"
},
"source": [
"#### Coordenada de una categoría en función de las coordenadas de los individuos \n",
"\n",
"$$ \n",
"G_s(j) = \\frac{1}{\\sqrt{\\lambda_s}} \\frac{1}{n_j} \\sum_{i=1}^n z_{ij} F_s(i)\n",
"$$\n",
"\n",
"- $I_j$ es el conjunto de individuos que asumen la categoría $j$, \n",
" - La categoría $j$ se sitúa en el promedio aritmético de las coordenadas de los individuos que la asumen, dilatada por el inverso de la raíz cuadrada del valor propio.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "ThYplWCmUX84"
},
"source": [
"### Representación simultánea en el primer plano factorial"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"id": "wxGwmRTXUX84",
"outputId": "5dd1320e-f481-4ddd-895a-7868e923f4f7"
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 4 × 17 of type chr</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>25</th><th scope=col>50</th><th scope=col>75</th><th scope=col>100</th><th scope=col>125</th><th scope=col>150</th><th scope=col>175</th><th scope=col>200</th><th scope=col>225</th><th scope=col>250</th><th scope=col>275</th><th scope=col>300</th><th scope=col>325</th><th scope=col>350</th><th scope=col>375</th><th scope=col>400</th><th scope=col>425</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>gene</th><td>F </td><td>M </td><td>M </td><td>M </td><td>F </td><td>F </td><td>M </td><td>F </td><td>M </td><td>M </td><td>M </td><td>M </td><td>M </td><td>M </td><td>M </td><td>F </td><td>M </td></tr>\n",
"\t<tr><th scope=row>estr</th><td>medio</td><td>bajo</td><td>bajo</td><td>medio</td><td>medio</td><td>bajo</td><td>alto</td><td>bajo</td><td>alto</td><td>alto</td><td>bajo</td><td>bajo</td><td>alto</td><td>medio</td><td>medio</td><td>bajo</td><td>alto</td></tr>\n",
"\t<tr><th scope=row>orig</th><td>Otro </td><td>Bogo</td><td>Bogo</td><td>Bogo </td><td>Otro </td><td>Bogo</td><td>Bogo</td><td>Otro</td><td>Otro</td><td>Bogo</td><td>Bogo</td><td>Otro</td><td>Bogo</td><td>Bogo </td><td>Bogo </td><td>Bogo</td><td>Bogo</td></tr>\n",
"\t<tr><th scope=row>edad</th><td>a17 </td><td>a18 </td><td>a17 </td><td>a18 </td><td>a17 </td><td>a16m</td><td>a19M</td><td>a17 </td><td>a16m</td><td>a17 </td><td>a17 </td><td>a19M</td><td>a17 </td><td>a19M </td><td>a19M </td><td>a18 </td><td>a16m</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 4 × 17 of type chr\n",
"\\begin{tabular}{r|lllllllllllllllll}\n",
" & 25 & 50 & 75 & 100 & 125 & 150 & 175 & 200 & 225 & 250 & 275 & 300 & 325 & 350 & 375 & 400 & 425\\\\\n",
"\\hline\n",
"\tgene & F & M & M & M & F & F & M & F & M & M & M & M & M & M & M & F & M \\\\\n",
"\testr & medio & bajo & bajo & medio & medio & bajo & alto & bajo & alto & alto & bajo & bajo & alto & medio & medio & bajo & alto\\\\\n",
"\torig & Otro & Bogo & Bogo & Bogo & Otro & Bogo & Bogo & Otro & Otro & Bogo & Bogo & Otro & Bogo & Bogo & Bogo & Bogo & Bogo\\\\\n",
"\tedad & a17 & a18 & a17 & a18 & a17 & a16m & a19M & a17 & a16m & a17 & a17 & a19M & a17 & a19M & a19M & a18 & a16m\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 4 × 17 of type chr\n",
"\n",
"| <!--/--> | 25 | 50 | 75 | 100 | 125 | 150 | 175 | 200 | 225 | 250 | 275 | 300 | 325 | 350 | 375 | 400 | 425 |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| gene | F | M | M | M | F | F | M | F | M | M | M | M | M | M | M | F | M |\n",
"| estr | medio | bajo | bajo | medio | medio | bajo | alto | bajo | alto | alto | bajo | bajo | alto | medio | medio | bajo | alto |\n",
"| orig | Otro | Bogo | Bogo | Bogo | Otro | Bogo | Bogo | Otro | Otro | Bogo | Bogo | Otro | Bogo | Bogo | Bogo | Bogo | Bogo |\n",
"| edad | a17 | a18 | a17 | a18 | a17 | a16m | a19M | a17 | a16m | a17 | a17 | a19M | a17 | a19M | a19M | a18 | a16m |\n",
"\n"
],
"text/plain": [
" 25 50 75 100 125 150 175 200 225 250 275 300 325 350 \n",
"gene F M M M F F M F M M M M M M \n",
"estr medio bajo bajo medio medio bajo alto bajo alto alto bajo bajo alto medio\n",
"orig Otro Bogo Bogo Bogo Otro Bogo Bogo Otro Otro Bogo Bogo Otro Bogo Bogo \n",
"edad a17 a18 a17 a18 a17 a16m a19M a17 a16m a17 a17 a19M a17 a19M \n",
" 375 400 425 \n",
"gene M F M \n",
"estr medio bajo alto\n",
"orig Bogo Bogo Bogo\n",
"edad a19M a18 a16m"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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AIQgAAEIAABCEAAAokigIKUqOlkMBCAAAQgAAEIQAACEIBAXQigINWFHudCAAIQ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\n/Phsa1iGAAIIIBAXAQKkuNxJrgMBBBBAoN4CQ4aYDRuW+zBu2jc766zc6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gQQQAABBBBAAAEEEKinAAFSPQHZHQEEEEAAAQQQQAABBOIj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\nCCCAAAIIIIAAAghEV+D/AVo1ghMUpYwLAAAAAElFTkSuQmCC",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plot(acm,roweti=sel,main=\"Representación simultanea 1er plano\",gg=TRUE)\n",
"t(Y[sel,])"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "rbsVdEwWUX84"
},
"source": [
"### Plano factorial 2-3"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"id": "iMnIqUzbUX84",
"outputId": "29ca5b31-7f35-49e9-e132-a87f0fa48dbd"
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 4 × 17 of type chr</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>25</th><th scope=col>50</th><th scope=col>75</th><th scope=col>100</th><th scope=col>125</th><th scope=col>150</th><th scope=col>175</th><th scope=col>200</th><th scope=col>225</th><th scope=col>250</th><th scope=col>275</th><th scope=col>300</th><th scope=col>325</th><th scope=col>350</th><th scope=col>375</th><th scope=col>400</th><th scope=col>425</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>gene</th><td>F </td><td>M </td><td>M </td><td>M </td><td>F </td><td>F </td><td>M </td><td>F </td><td>M </td><td>M </td><td>M </td><td>M </td><td>M </td><td>M </td><td>M </td><td>F </td><td>M </td></tr>\n",
"\t<tr><th scope=row>estr</th><td>medio</td><td>bajo</td><td>bajo</td><td>medio</td><td>medio</td><td>bajo</td><td>alto</td><td>bajo</td><td>alto</td><td>alto</td><td>bajo</td><td>bajo</td><td>alto</td><td>medio</td><td>medio</td><td>bajo</td><td>alto</td></tr>\n",
"\t<tr><th scope=row>orig</th><td>Otro </td><td>Bogo</td><td>Bogo</td><td>Bogo </td><td>Otro </td><td>Bogo</td><td>Bogo</td><td>Otro</td><td>Otro</td><td>Bogo</td><td>Bogo</td><td>Otro</td><td>Bogo</td><td>Bogo </td><td>Bogo </td><td>Bogo</td><td>Bogo</td></tr>\n",
"\t<tr><th scope=row>edad</th><td>a17 </td><td>a18 </td><td>a17 </td><td>a18 </td><td>a17 </td><td>a16m</td><td>a19M</td><td>a17 </td><td>a16m</td><td>a17 </td><td>a17 </td><td>a19M</td><td>a17 </td><td>a19M </td><td>a19M </td><td>a18 </td><td>a16m</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 4 × 17 of type chr\n",
"\\begin{tabular}{r|lllllllllllllllll}\n",
" & 25 & 50 & 75 & 100 & 125 & 150 & 175 & 200 & 225 & 250 & 275 & 300 & 325 & 350 & 375 & 400 & 425\\\\\n",
"\\hline\n",
"\tgene & F & M & M & M & F & F & M & F & M & M & M & M & M & M & M & F & M \\\\\n",
"\testr & medio & bajo & bajo & medio & medio & bajo & alto & bajo & alto & alto & bajo & bajo & alto & medio & medio & bajo & alto\\\\\n",
"\torig & Otro & Bogo & Bogo & Bogo & Otro & Bogo & Bogo & Otro & Otro & Bogo & Bogo & Otro & Bogo & Bogo & Bogo & Bogo & Bogo\\\\\n",
"\tedad & a17 & a18 & a17 & a18 & a17 & a16m & a19M & a17 & a16m & a17 & a17 & a19M & a17 & a19M & a19M & a18 & a16m\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 4 × 17 of type chr\n",
"\n",
"| <!--/--> | 25 | 50 | 75 | 100 | 125 | 150 | 175 | 200 | 225 | 250 | 275 | 300 | 325 | 350 | 375 | 400 | 425 |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| gene | F | M | M | M | F | F | M | F | M | M | M | M | M | M | M | F | M |\n",
"| estr | medio | bajo | bajo | medio | medio | bajo | alto | bajo | alto | alto | bajo | bajo | alto | medio | medio | bajo | alto |\n",
"| orig | Otro | Bogo | Bogo | Bogo | Otro | Bogo | Bogo | Otro | Otro | Bogo | Bogo | Otro | Bogo | Bogo | Bogo | Bogo | Bogo |\n",
"| edad | a17 | a18 | a17 | a18 | a17 | a16m | a19M | a17 | a16m | a17 | a17 | a19M | a17 | a19M | a19M | a18 | a16m |\n",
"\n"
],
"text/plain": [
" 25 50 75 100 125 150 175 200 225 250 275 300 325 350 \n",
"gene F M M M F F M F M M M M M M \n",
"estr medio bajo bajo medio medio bajo alto bajo alto alto bajo bajo alto medio\n",
"orig Otro Bogo Bogo Bogo Otro Bogo Bogo Otro Otro Bogo Bogo Otro Bogo Bogo \n",
"edad a17 a18 a17 a18 a17 a16m a19M a17 a16m a17 a17 a19M a17 a19M \n",
" 375 400 425 \n",
"gene M F M \n",
"estr medio bajo alto\n",
"orig Bogo Bogo Bogo\n",
"edad a19M a18 a16m"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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+9tsv2NuvvwbP6rL8tdfMjjmmJDjSHHUYseqqBEeBEn8RQAABBBAo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66yudkMn1rlJlKzAEihSBTM8l3LWJlUSY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\nqJeIadBfzkU0bsRTS5OncRupczRGybv11ltzOZTEa5mLXSI0eT1gLnZ5hd8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YAuWAAN47+lisUi6+WDQeospqea3AM7xHjx6OQpmO4Mr0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\nlx8p4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BaBJlmdspd8+ee+7pzMvu9JHq\ntK3w7opWJ8VEylNYZsyYYR06dAgXFXVbylI2kSKi30anx6VJ9DdQPr6agkznrrkmrapfIdIK\nU1hkGu5SMKWJput0Ri/uI+FXqPTbfMABytW0gjVr1sz9mU2enKyjNjfbLK2JjB2taMl/KioR\n3NHD7EOgqggsVVWzYTJpBAJb5AEDksELZIssR09nveCe0i3WkBSQQF+YUjD0hEq+sltumVQE\nwg3KhE2rLzJTU6AF+e9I+ZJvT/TJklJC7LCD2SuvJL/Q//EPc46i4dZybxfSj56w6Qu/DtN2\n/1RNCmHU/E5P9GSmIIUnLPoR2H//5A9ENAiDVo+6dUs+oQufwzYEGouAnpbr5lA3f3qiXo0i\nEyXNL/j7lxwzEAhkIbCvnmQ5+ULOn05WdVnCtWIzXTZrEZnmvrCzmd5FqhV9V1Z+2eKx6Pcm\nLLLKU5msHxQ+O/ynB49//GO4dtKXKb0kqWAFZYGVn1tIc35PCf8XtOlyVNshh8gMMaid+1W/\ngVKqon/RB6u5W+AIBCqfACtIlX8Nc84gsEV+5BGz3XZLVtNTJDmEnnhiK7eqlFyCP+ggczbK\nZoqkoy9RiRxGnZ+sX5pPliQVKJfA3j25NfeULlmqHwI91dLTryAyq8zeFMRLilmgOOmLO0fu\nzKD51KsUtXz60Qn5KF3K6aD27r8/fUXoiSfMJRZMmiWkOl+0oWAPF19szgY+fTVNCpLLR+if\n+kXPYR8CS0pAN3/favl0kYwfP94rEbmcqXs7j+1X9BRikcjs6Fe92WMsrd0dm8ykwqKknxtu\nuKFtv/324WK2a4SATNWucFEM1nNP4JTwNSxB8lcFYZB0kV2Zk7EulOgWsiVbJBMnTvQrS3of\nlVu0sCmrDUX6D1sCRvNEa5VJ9fSbp+BBYdEDyGxKVrhOdDvIp6vnKrfc8ot7OPiT90Fq3bqZ\nLViQtByR8lMsUZTCndwTUwXakHTr1s2Hdi9Wf7QLgWISYAWpmHTL2HbYFjlQjjScwBb5/feb\n2ZtvNjFnkWDPP28uR8Vi5Uj1jj3WnPmKthaLVoEef3yxcqQj8lVVVB0pSoFIIdOTJtlKByJL\nhHxz6OXbT9B2fa/9+iVXsbSqJbM5hVqV6Z/Gpx+gcCS7oC2ZImrFKRxxT6Z6LlWHV5CCerxC\noLEITJkyJU05Crf7G4VNjIjMj8LKkQ7rybpWZeIquhGOKkfBWPfZZ59gk9caIyDfoctcpAFF\nr5P5XFhuueUW54/T0q2mJJdT9nP20Ms4cwiZ3YVF+3pAEKw4hY+VeltvZVkfDBuW3rMi2YVF\n/q6SaGTyjz9OripFI9kla+f+LwXJPWMx/QbrHiAsMhfXSpUecBZDpKAqwEagHKkPPeBZPuxc\nVYyOaRMCRSLQrEjt0myZCYRtkV201DQJbJE//zx5I6WoOjK7C4vusaQkvPTS4tJttjEXqcdc\nRKGkWZrsp2WOJxM3masFogg6q61mFo0AF7W/DupHX/PtJ3pern2tIClSnZQ+rQzJhlsPuBRh\nyJmzex+pbOcGq0j6oZNZglaP9JRPUYNkBohAoDEJ/CkIQ5Wl0U+zJCR7TFp+hUldY86lOFXY\nFBluAwg0d1/Kp7vwbMofJgVHiWLla6QIdk899ZQpQesqq6ziW1a5ksle48wWVnM/NHu4/A6j\n3RfyOS5s3ABnttBLTqRlFn2U9ZtzxBHJ38ju3c2efNJMVguS4BmGFCBZa0hx0sNGmaXLz1Uh\nwhWkIfyQMXlm3f9lEicTePnb7rdfc2cp0txZeyzl8ypJn3QLtSlTc4fV/wbqdzGw/qi79bqP\n7qh441lEppAfOTt2rQ4iEKgkAihIlXS1Chhr2BZZNshhkRldp07znAKzlH/KpWPROiqLKji3\n3po0u5N1jNqQAqUveJmuKXFqIFIo8mkvqB99zbef6Hl17ffrl/RTUuAImdUpuIMi0a2zTvKJ\nW7ZzpSAp6pCCOCiruBTDQp/oZWuXMghkIyDToCeCO6hIBfkkFSIKOZzLgbyQdhq7rp7+99OH\nMYvwpDkLlBoqOsvZmSmgwGCnHYwaNcrPXMrQjS4MaTSZ6eUudrbMTqUU6byOHTv6SHc6Nw4i\nReWFF8xOOSWZ9FW/aVotUuR/KUHB72NQT1HrFL5bSWUlWglSZNZFOmGyMM//MpmXZcTAgUs5\nJcmZbjjR18dhh6WH6Jb1iIItuYXrRhGtIOWSES6sHwpSLjqUx5UAClJcr8wSjitsixyxRPC2\nyDNmKFRq61TUN+VTiIqSqwaigA8yw5NSJIVhkTm4PywzAtlaB6I6Upq0MhU8KdOxcHtB3ehr\nIf1Ez821P3dusm9F51O+pEDk6iGbcGU5zyZKGivLJs1FTwD1/a8fHwQCxSCgp+QXKjxiFjk/\nGh84S51wURyVI42vlcuYqZvZ77KEm3w5nD0zPJnItuamlQPdTCOVR+ClsFlCaPgyDdUq0slO\nSxjnktZpVamrvrSziI5pBUlmeaq7rjMTyBb2O8upJSnS21vJYRWdLiyBu2A4jZK2ZZ0gqwbF\noVCABVlghH871YZ8lbKJFKmoKK7FLrvMdeZ0M5xJeRv3O9YqpZQFdVVHv9FRaagLY7du3XIm\n6T2IH84oZvYrgMBSFTBGhtgAAvXZInfuvLy3RVaIbPklyQY6/GWpyHbyTQpEpnT64lSG77By\nJAVDq0fhL1Vl8dbTqWgeIf0I1CeF9FNfW8FxhVyVP1U427iOybRBT9r0ZC2XaBVJ4U5vuMFs\nk00y/bJynUc5BBpCQE/Lo6KkmQpiEJVKXXGZ7Gx8N9JTlEUiRUdmVLrJzUcuclk033DZLgOn\n/XzOoU7lEND7YW3nAJpLOQrPRL5IPZzdc5yUI41Pv6dSdP773/Bok+khVBL4HoWPOp3PP5DT\n72tUOQrXK2S7ffuFrs1EhnJUSBv51n02W1xwd7IiVhKOP1+K1IsTARSkOF2NRhyLHq7KFlmr\nJ85E2ys7yqCtJX+tKB155LyULfJNN5l98EHSP0eBCKQY7bxzevACraToC/zmm5MBDlwOP29y\n5nwyvWIls7sg2IGcQRV2W/bXd9yRtKnWg/FongdNVwqX/HqCFahC+skXl0KWy6ROwR80dylh\nynIuawwxyuL/nmpa4b41LylXPARLYWGjSARkSiTTISlKA52TnLbfz5FwS4kzs5ne5Yp4V6Qh\nN6jZt91TC41Tf7+4DxjR6xqEkZNiSkB59RSYSL9v+t3429+S1hcjRyYju0YDIMV0GgUNS4rQ\nWy4UrlaJA1nfmWEo+AwCgUok4G6jkWoloC9mrZCceGJSQdA8A1vk005zjjiWdE6SMiQlyT2Y\ndQ6uyTp9+yaDEShqnUQrTTKlkzOpvvSl0CjAgZQOKU5Shl54wdyNTnJfmcRlknfMMckkdlql\nkrIUDVSlFSjZQbv7JC+F9JM8I7//zmTd54BQNnGJzOf++c+kT1WyJPt/mdYpKIPuUbWahECg\nFASkKOUjCxS7F4EABGJFwFmbmYIVKY6K3KlkVahor/rNccEnq1Z+5yIx/fzzz1U7PyZWWwSa\nuCd4i25Na2vicZntJOeYc4pb1hmezZC4EQcpm2iF4tYXtxxE9fRZ+Uhkyx2W8eOTT74UDjSX\nyPxOobKlzNQngf9PkF+pvvrh44X0Ez4v17be6fIjknKXw7Q916klKVf+G5mXyDEZiQcBRVaT\nEqIwxEg8COi7a677YtHnBD+keFwThZdXYBC+u+JxPTQK5Y9anAcp+TA0PqOr3ZHoc9LWhf3l\nu6s87wFZLPTp08e5Tjxb7wAwsasXUXVUcH7RLorM4ug5uWYlBaou5UjnKUlsPsqR6joT8VTy\nWe0XIoX0k0+7suvWuOOoHOUzfupAoJYJvPrqq15RXdHF3Jf/0TFankYgAAEIQAACRSCAglQE\nqDQJAQhAIM4EFG5b/ktybu8uO9KYi3yWtnTOhDNnzvQj1YrFTc4uGN+lmF84hgcBCECgQgng\ng1ShF45hQwACEKiPgExsFAY5HDWug1uaDTtOKwmtQiznY239mcsK3aVLF7cy7JaGSygyicgm\nzzzzTLZiyiAAAQhAAAJLRIAVpCXCx8kQgAAE4klAttZ7uBCWB4SiiygiXlg5Co9cSk+QoDNc\nrtUahRlX2GWF4pb9/IEHHuh9HML1irktu/1cIiUQgQAEIAABCDQmARSkxqRJWxCAAARiQEAO\n2oqEN3r06LTRnHDCCWn74Z35LlPl7i5E5StBNstFBy93ISCHDh1qAwYMcOkAPvDbD7ps0TLT\nK5W0bNkyZ1eVmg8q54Q4AAEIQAACZSeAglT2S8AAIAABCDQegRdffNF++9vf+siYbSIRV5R0\nNpcoUp8iW/7rX/9KVZngEp4NGjTIK1snn3yyC4+/vh1//PF23nnnuRDGj7lQxi6WcQnkCuUX\nyCKrrbZallKKIAABCEAAAktGAAVpyfhxNgQgAIFYEdjWZUWWed1zzz3ncni5JF4hueqqq0J7\n6Zv33HOP7b333vboo4/6NAA6OtJltlSo875KjBaSYP/2228PlRZvU6thMvMLiyLZTVTcfgQC\nEIAABCDQyARQkBoZKM1BAAIQKCeBa6+91hRMYauttso6DJnMRWXPPfe0HXfc0Xr06GG//vqr\nffzxx77KO++8419VHhYpJ8suu6xLoOwyKJdILr74Yh9IYp9F2aaff/75EvVMNxCAAAQgUGsE\niGJXa1ec+UIAAlVN4Kijjqpzflphkhx22GG2zTbbWL9+/fy+/inHkOQHZZV2oqSsCgUelPvC\nRf9UFtQLl7MNAQhAAAIQqHQCrCBV+hVk/BCAAAQKICCTOcmGG26YphypTH5Iknnz5vlX1dVK\nkZSkqKhuUC96jH0IQAACEIBAJRPI/NWr5NkwdghAAAIQqJNA+/bt/fEg6Wq48owZM/yugjVI\nVHfWrFlZcySpblDPVy7RPwWRUOLYzp07l6hHuoEABCAAgVojgIJUa1ec+UIAAjVNYNVVV/Xz\nnzZtWgaHoCwwqVNd5UGaPn161rpBvYyDRSxQWO+VV17ZmjZtWsReaBoCEIAABGqZAApSLV99\n5g4BCNQcASWE1crQ2LFjM+auMpnTBeHAu3Tp4utE6yp6nFaWZKaHQAACEIAABKqNAApStV1R\n5gMBCECgHgIK0PDss8/at99+m6qp5LIjRoywXXbZxfsd6YCSwUqhuvPOO1P1tKF9KVL77rtv\nWjk7EIAABCAAgWoggIJUDVeROUAAAhAogMDAgQO9idpOO+1kL7zwgo0ZM8Z23XVXW7BggYVz\nJWml6fDDD7drrrnGLrjgAvvoo4/89jnnnGMDBgywXr16FdArVSEAAQhAAAKVQYAw35VxnRgl\nBCAAgUYjoAAHyiN0yCGH+FDfWg36/e9/b8OGDcsIfqC8SYlEwqQUnXXWWdaxY0fr37+/DR48\nuNHGQ0MQgAAEIACBOBFAQYrT1WAsEIAABBqRwEsvvZSztS233NLGjRtn8idaeumlveKTrXLz\n5s39qtFll13m66+77rpZw35nO5cyCEAAAhCAQCUSwMSuEq8aY4YABCDQSAQ6deqUUzkKdyFf\npB49epRdOZKpn/ykwv5T4XGyDQEIQAACEFhSAihIS0qQ8yEAAQhAoGQEtOr1zjvvkKS2ZMTp\nCAIQgEDtEUBBqr1rzowhAAEIQAACEIAABCAAgRwEUJBygKEYAhCAAAQgAAEIQAACEKg9AihI\ntXfNmTEEIAABCEAAAhCAAAQgkIMAClIOMBRDAAIQgAAE6iPw5Zdf2uTJk+us9tlnn9ncuXPr\nrKOD+dartyEqQAACEIDAEhFAQVoifJwMAQhAAAK1SkBh1NdZZx276KKLMhAsXLjQTj31VOva\ntaspNHrbtm3twAMPtDlz5qTVzbde2knsQAACEIBAUQmgIBUVL41DAAIQgEBjEjjmmGPs+uuv\ntw4dOjRmswW3NWPGDDv00ENNCk42UYLdoUOH2oABA+yDDz7w2w8++KDtt99+adXzrZd2EjsQ\ngAAEIFBUAiSKLSpeGocABCAAgcYksPHGG9t6661nrVq1asxmC27r+OOPz6kcTZgwwQYNGmRH\nHHGEnXzyyb7t9ddf32bOnGlnnHGGvffee9azZ0/Lt17Bg+MECEAAAhBYIgKsIC0RPk6GAAQg\nAIFaI3DPPffYXXfdZTfffHPWqY8cOdJmz55tffv2TTse7N9+++2+PN96aY2wAwEIQAACRSeA\nglR0xHQAAQhAAALVQmDixIl27LHH2llnnWWbbbZZ1mkpka2kR48eaceOYzpbAAA2QElEQVQ7\ndepkyy67rL3//vu+PN96aY2wAwEIQAACRSeAglR0xHQAAQhAAALVQCCRSNhhhx1ma665pjeh\nyzWnH3/80ZZaailbccUVM6qo7IcffvDl+dbLaIQCCEAAAhAoKgF8kIqKl8YhAAEIQKBaCFx6\n6aU2ZswY08pPs2a5fz5lXqeVIilJUVluueVs3rx5vjjfetE22IcABCAAgeISyPz2Lm5/tA4B\nCEAAAhCoOAIKrCCzuiFDhviw3XVNoH379jZr1izTilNUFP2udevWvjjfetE22IcABCAAgeIS\nQEEqLl9ahwAEIACBRiRw77332jnnnGPTpk1rxFbrb+q0007zCs9rr73mzexkanf00Uf7E0eN\nGuXLdEyy6qqr+gh306dP9/vhfxp3YHqXb73w+WxDAAIQgEDxCaAgFZ8xPUAAAhCAQCMRePrp\np+2GG24wrcSUUqTUrLHGGvbGG2/Y66+/7v/eeustP4TvvvvO70+dOtXvd+nSxb+OHTs2bYgK\n8KCVpQ033LCgemmNsAMBCEAAAkUngIJUdMR0AAEIQAAClU5g+PDh9sknn6T9BQqSVpN0bOed\nd/bTVDLYZZZZxu688860aWtffkn77rtvQfXSGmEHAhCAAASKTiC3l2nRu6YDCEAAAhCAQPUR\nkG/R4Ycfbtdcc42tttpqtscee9jo0aO9aeCAAQOsV69eftL51qs+QswIAhCAQLwJoCDF+/ow\nOghAAAIQqEACl19+ufdZkr+Ugjt07NjR+vfvb4MHD06bTb710k5iBwIQgAAEikoABamoeGkc\nAhCAAASqlUCbNm2yRqrTfJs3b+5XkC677DIbN26cj3yXLex3vvWqlSHzggAEIBBHAihIcbwq\njAkCEIAABKqCgHyRevToUe9c8q1Xb0NUgAAEIACBJSaAgrTECGkAAhCAAARKRWD77bf3YbKV\ncBWBAAQgAAEIFIMAUeyKQZU2IQABCECgKAT2339/O++881K5hIrSSahRheY+4IADbNiwYaFS\nNiEAAQhAoJoJoCBV89VlbhCAAAQg0GACbdu2tc6dO5uS0/bt29eaNGliH3/8cYPb40QIQAAC\nEKgMAihIlXGdGCUEIAABCJSQwMYbb5w1Ge16661XwlHQFQQgAAEIlIMAClI5qNMnBCAAAQjE\nmsDbb78d6/ExOAhAAAIQKB4BFKTisaVlCEAAAhCoQgJTpkypwlkxJQhAAAIQCAigIAUkeIUA\nBCAAAQgsIqCw27mkffv2uQ5RDgEIQAACVUAABakKLiJTgAAEIFArBN58800bOXKkzZ49u6hT\n/vrrr7O2v8suu2QtpxACEIAABKqHAApS9VxLZgIBCECg6glcd911dvTRR9v3339f1LlqlWju\n3Lm20kor+X6WXnppu/HGG71yVtSOaRwCEIAABMpOgESxZb8EDAACEIAABOJIoEWLFoa/URyv\nDGOCAAQgUFwCrCAVly+tQwACEIAABCAAAQhAAAIVRIAVpAq6WAwVAhCAAAQgEAcCMj+86qqr\nbPLkyXbAAQdY165d4zAsxgABCECgUQiwgtQoGGkEAhCAAAQg0DACb7zxhm233XZ25ZVXNqyB\nEp81evRoa9OmjZ188sl2ySWXWK9evax///4lHgXdQQACECgeARSk4rGlZQhAAAIQgECdBOTn\ntOmmm9pzzz1nAwYMsCZNmtiXX35Z5znlPrjzzjvbggUL0oahyILDhg1LK2MHAhCAQKUSQEGq\n1CvHuCEAAQjUIIHVV1/dNtpoI5NiUemiucyfPz9jGmuttVZGWVwKxo4daz///HPW4SjCIAIB\nCECgGgigIFXDVWQOEIAABGqEwJlnnmmPPfaYrbLKKhU/4/Hjx1fcHJZaKvdtg1a/EAhAAALV\nQCD3N101zK4Mc5g0aZLdd999ZeiZLiEAAQhAAALFJbDuuuta69ats3Zy3HHHZS2nEAIQgECl\nEUBBasQrNmvWLDv99NNt1KhRjdgqTUEAAhCAQDUSUPLZShT9xkXHvueee/podpU4H8YMAQhA\nIEqAMN9RIg3cf+2112zIkCH2008/mezKEQhAAAIQgEBdBL766ivr3LlzRpVjjz02oyxOBb17\n97YZM2aYfI4U5vuggw6qCpPHODFmLBCAQHkJoCA1Av+ZM2ea7OL1IyEZM2ZMI7RKExCAAAQg\nUM0EOnXqZMon1K1bN/v++++tefPm9vjjj9s222wT+2kvs8wyNnDgQD/OhQsX2tSpU2M/ZgYI\nAQhAIF8CKEj5kqqjXsuWLe3ee++1du3a2a233lpHTbNXXnnFvvnmm1Qd/Tj++uuvNnv27FRZ\nKTYUolV9R0O1lqJv+shNQDcapX4v5B4NRxRhrByfT8jnJqDrIdH3V10BA3K3EL8j0bDelfYd\nkEgkjO+ueL2vguiIeiV4Rnyujb6/5syZY02bNo3PoGpoJL/88ovp+yofQUHKh1I9dZo1a+aV\no3qq+cN33nmnPfvss6mqHTp0sI4dO9r06dNTZaXaQDkqFen8+9FNRjneC/mPsDZrBjcbtTn7\neM1aZszBgyVuMuJ1bfjuitf10Gj0WdEfEh8C8ldHykNA970oSEVgP23aNHvqqadSLUu52Xbb\nbVP7+WwccsghtvXWW6eqzps3z5Rgr23btqmyUmwoj4XyiEi5Q+JBQDcXeiKuDPVIPAgEK0ha\nJUbiQeCEE06wESNG2Icffoi/ZzwuiV890m8K310xuSBuGPru0kqFTCGrIWdYfMgu2UikHOn3\nhIc7S8axoWdrBSnfFVXujgugrBvYRx55JHVG9+7dC1aQ5NwaFoUFf+KJJ6xVq1bh4qJvSzHT\nF6ds3pF4EAgUpFK/F+Ix+/iOQk+cuCbxuT7Bj5tu+rgu8bguWvnWzTjXIx7XQ6PQ50TXRL/x\nXJf4XBddEylIPJwuzzVBQSoSd0WnGz58eJFap1kIQAACEIAABCAAAQhAoNwEyINU7itA/xCA\nAAQgAAEIQAACEIBAbAigIMXmUjAQCEAAAhCAAAQgAAEIQKDcBPBBauQr0K9fP9MfAgEIQAAC\nEIAABCAAAQhUHgFWkCrvmjFiCEAAAhCAAAQgAAEIQKBIBFCQigSWZiEAAQhAoPEJXH/99TZx\n4kTr1q1b4zdOixCAAAQgAAFHAAWJtwEEIAABCFQMAYUvVr4wBAIQgAAEIFAsAvzKFIss7UIA\nAhCAAAQgAAEIQAACFUcABaniLhkDhgAEIAABCEAAAhCAAASKRQAFqVhkaRcCEIAABCAAAQhA\nAAIQqDgCKEgVd8kYMAQgAAEIQAACEIAABCBQLAIoSMUiS7sQgAAEIAABCEAAAhCAQMURQEGq\nuEvGgCEAAQjULoHTTjvNevXq5UN91y4FZg4BCEAAAsUkgIJUTLq0DQEIQAACjUpg2rRpNmnS\nJFuwYEGjtktjEIAABCAAgYAAClJAglcIQAACEGgQgauvNnv33QadykkQgAAEIACB2BFoFrsR\nMSAIQAACEKgYAm5BxwYNMlt/fbMXX6yYYTNQCEAAAhCAQE4CrCDlRMMBCEAAAhCoj8DZZ5tJ\nSRo92uy+++qrzXEIQAACEIBA/AmgIMX/GjFCCEAAArEk8NFHZtdeu3hop5xiNnfu4n22IAAB\nCEAAApVIAAWpEq8aY4YABCAQAwInnmj266+LBzJhgtkllyzeZwsCEIAABCBQiQRQkCrxqjFm\nCEAAAmUm8PDDZs88kzmIiy4yF2Uus7yxSk499VR78MEHbZVVVmmsJmkHAhCAAAQgkEYABSkN\nBzsQgAAEIFAfgfnzzU46KXutn382c6mKiiZrr722bbbZZtaiRYui9UHDEIAABCBQ2wRQkGr7\n+jN7CEAAAgUTuOwysy+/zH3a8OFmr76a+zhHIAABCEAAAnEmgIIU56vD2CAAAQjEjMDkyWaD\nB9c9qETCbOBAM70iEIAABCAAgUojQB6kSrtijBcCEIBAGQkonPcuu+Q3gA8/NNtgg/zqUgsC\nEIAABCAQFwIoSHG5EowDAhCAQAUQ2H9/M/0hEIAABCAAgWolgIldtV5Z5gUBCEAAAhCAAAQg\nAAEIFEwABalgZJwAAQhAAALlInDDDTfYcccdZ1OmTCnXEOgXAhCAAASqnAAKUpVfYKYHAQhA\noJoIvP766/bQQw/Zz4onjkAAAhCAAASKQAAFqQhQaRICEIBAsQjMnWv20UdmP/7YeD18/bXZ\np582XnvRlhSs4YcfoqWL92fMMHvvPbNp0xaXsQUBCEAAAhAoFwEUpHKRp18IQAACDSAgZWP9\n9c3uvbcBJ+c4xVms2dZb5zi4hMVPPGHWs6fZU09lNiSlSQEf2rY123BDs3btzLbf3mz8+My6\nlEAAAhCAAARKRQAFqVSk6QcCEIBAjRF4+WWzgw4yW7gw+8QPO8zsgQfMzjzT7I03zC680GzM\nGLM99jCbPz/7OZRCAAIQgAAEik0ABanYhGkfAhCAQI0RkHuQEsVutZVZkybZJ//dd2ZaXdp1\n12Ti2U02MTv9dLP+/c3efz+pKGU/k1IIQAACEIBAcQmQB6m4fGkdAhCAQAYBrY5cf73Za6+Z\nzZplttFG5iKzma20UkZVe/pps8ceM5s0yWzbbc1+97vMOip58EGzF180+/xzs+WXN+vRw+z4\n481WWCG9/jffJOs+95xZ165JhSS9Ru69b781u/lms08+SfoLrbFGMmlsnz7p5wwdanbllWZH\nH508vttu6ce1N29esqxTp/Rj666b3CcGQzoX9iAAAQhAoHQEWEEqHWt6ggAEIGBaOdl0U7MB\nA8zeecdsmWXM/vMfsw02MHvrrXRAF1xgtsMOZq+8Yta8udk//mF21FHpdbS3775m++xjJqVH\n/jyqP2iQ2W9/azZ79uL6339vttlmZmedZbb00mbvvmu25ZbJoA+La2XfGj3abL31zC65JBkg\n4pdfkkreTjuZ/fvf6ef07m0mX6lrrjFr2TL9WLDXpUvS72j4cLMPPkiWKljE1VebLbdcbp+o\nfd1kz3ITWCGq+QUN8woBCEAAAhBYQgIoSEsIkNMhAAEIFELgtNOSEdseeSSpRNx1V1JBaNEi\nueIS+OtoNUhKjhQpF9nahg1L1l+wIL23Z59N+vGcemrSNE0Kx7hxZiedZDZxotmjjy6uL3+g\nmTOTitjddycVqosuyi8ogpSqX39NRrsbOTIZdEGrWhq3FKGwaKVLK1j1yTPPJBU0KXJrrWW2\n+upJk7w338ytWO24445uZex4pwg6TRCBAAQgAAEIFIEAClIRoNIkBCAAgWwEfvrJ7PbbzbbY\nwixsdrbyymaHHmr29tvJYAU6VwpU06Zm5523uCVFeVNAg7Css47Z/fcnV4XC5Qp0IAnCayuU\n9vPPmx15pNmaayaP6f+xxyaVk8Ul2be0evX442YdOiw+LpNArRYFfSw+kt+WzAelDEnXkQ+S\n2vvqKzMpTggEIAABCECgXATwQSoXefqFAARqjoD8gxKJpP/OXnulT3/y5OT+Z58lzeCUF2i1\n1TJ9iKI+SJ07m+nv1VeTyob8g8aOTa46qUWZwkkU+EB9y5QvLAqiIB+ol14Kl2Zub7ON2dSp\nZvfckzTJU94kmehpvA1ZzFF/WtE6+GCzG24wa9UqOdZzzkn6Y8kEUMocAgEIQAACECg1AVaQ\nSk2c/iAAgZolIAVDIh+b1q3T/7Sqc8ghZiuumKyjpKmqE5Wo68306clVHPkSKQqcFCH5Csk8\nLyxBEtZ82gyfF2zfequZ/IYOPNBMZnwyBVQQhs03D2oU9qoVMolMA6UcSaQUnXJK0rzu4YeT\nZfyHAAQgAAEIlJoAK0ilJk5/EIBAzRJQ1DeJfG3uvDO5HfyXb5FM6oKw2FrVkemcVn2CMtWV\n309Y/v73ZFCGG280+9OfzJot+lYPFJDAp0ntSRQIISrRNqPHFVhCqzlqQ9HywpHn5BsV9BE9\nr679L75I+i/95jfptaQAqn2tgiEQgAAEIACBchBgBakc1OkTAhCoSQJSkFZdNelfJH+ksBx+\nuFmbNskw3SpXpDv5DT30ULiWmYIrhEU+PIqEJx+mQDnScQVSkCiwgkRmePJ1kg+UlK5AFNlO\nvkl1iUzp1M7uu6crR/IXkiIT9FFXG9FjUrYU6vvJJ9OPyFRQpoiBQpd+lD0IQAACEIBA8Qmg\nIBWfMT1AAAIQ8ASkwChM9ty5ZgqiIMXkjTeSZmVaUVLeorXXTsKSwqREq0ccYXbHHckIdhde\nmBkxToqE2lN0PPkFjRmTjHwnRUgiE7xAbropGTHvgAOS/krqf+edF/spBfWeeioZhS4I361V\nHoUZVw4k5WSaMCHpi7TddkllS6HEA1+noI36Xv/yl6SyJbPC665LmgaKTd++SYUvHJwi3NZz\nLpb5zW4gM6Q9IhCAAAQgAIEiEFhkjFGElmkSAhCAAAQyCCgwgXxtTjwxmfhVFWRad9hhZuee\nu7i6FJIRI5Kmbccck8xnpBUgKUvKeRTI4MFmMs+TX9Dll5st5R57KXHrxx8n2w+vDkkZkpKk\n0N69eiX7lULSs2cyQl3QpnQPBXuYMiVZotUnmdJdcUVyFUkmde3bJ/MyaZxS4l54wWz77YMW\n6n9VMludowS5ml8gGovGHDW9C47f5eKiP/DAA3aA0/JWDBy2goO8QgACEIAABBqBAApSI0Ck\nCQhAAAKFEFBiV/3Jt0chsrt1yx6QQWG95fOjFSL5CQXhucMmcvLZuf56s2uvTUaU69p1cQ6h\n8eMzR9Wvn5n+dEzty6wvKhpbuA8dD8YskzyZxklpCqR//2Ar8zVYZco8kpzPqFFms2Ylw3sr\nap/GhEAAAhCAAATKSQAFqZz06RsCEKhpAh07mumvPpGPUaAc5aqrlaPu3XMdzSyXUtYQCedB\nasj52c5ZdlkzJYtFIAABCEAAAnEg4H5SEQhAAAIQgAAEIAABCEAAAhAQARQk3gcQgAAEIAAB\nCEAAAhCAAAQWEUBB4q0AAQhAAAIQgAAEIAABCEBgEQF8kHgrQAACEIBAxRDYcMMNXVCHWdaq\nVauKGTMDhQAEIACByiLAClJlXS9GCwEIQKCmCRzvkkXdcsst1qEY0SJqmiyThwAEIACBgAAK\nUkCCVwhAAAIQgAAEIAABCECg5gmgINX8WwAAEIAABCAAAQhAAAIQgEBAAAUpIMErBCAAAQhA\nAAIQgAAEIFDzBFCQav4tAAAIQAACEIAABCAAAQhAICCAghSQ4BUCEIAABCAAAQhAAAIQqHkC\nKEg1/xYAAAQgAIHKITBhwgR7//33bf78+ZUzaEYKAQhAAAIVRQAFqaIuF4OFAAQgUNsEzj//\nfOvTp4998803tQ2C2UMAAhCAQNEIoCAVDS0NQwACEIAABCAAAQhAAAKVRgAFqdKuGOOFAAQg\nAAEIQAACEIAABIpGAAWpaGhpGAIQgAAEIAABCEAAAhCoNAIoSJV2xRgvBCAAAQhAAAIQgAAE\nIFA0AihIRUNLwxCAAAQgAAEIQAACEIBApRFAQaq0K8Z4IQABCNQwgTZt2tiKK65oSy3Fz1cN\nvw2YOgQgAIGiEuAXpqh4aRwCEIAABBqTwNChQ+3DDz+0Ll26NGaztAUBCEAAAhBIEUBBSqFg\nAwIQgAAEIAABCEAAAhCodQIoSLX+DmD+EIAABCAAAQhAAAIQgECKAApSCgUbEIAABCAAAQhA\nAAIQgECtE0BBqvV3APOHAAQgAAEIQAACEIAABFIEUJBSKNiAAAQgAAEIQAACEIAABGqdAApS\nrb8DmD8EIAABCEAAAhCAAAQgkCKAgpRCwQYEIAABCMSdwLHHHmvdunWz8ePHx32ojA8CEIAA\nBCqUAApShV44hg0BCECgFgksWLDA5s+fX4tTZ84QgAAEIFAiAihIJQJNNxCAAAQgAAEIQAAC\nEIBA/AmgIMX/GjFCCEAAAhCAAAQgAAEIQKBEBFCQSgSabiAAAQhAAAIQgAAEIACB+BNAQYr/\nNWKEEIAABCAAAQhAAAIQgECJCKAglQg03UAAAhCAAAQgAAEIQAAC8SeAghT/a8QIIQABCEBg\nEYHBgwfbyy+/bJ06dYIJBCAAAQhAoCgEmhWlVRqFAAQgAAEIFIFAhw4dbLnllrNmzfj5KgJe\nmoQABCAAAUeAFSTeBhCAAAQgAAEIQAACEIAABBYRQEHirQABCEAAAhCAAAQgAAEIQGARARQk\n3goQgAAEIAABCEAAAhCAAAQWEUBB4q0AAQhAAAIQgAAEIAABCEBgEQEUJN4KEIAABCAAAQhA\nAAIQgAAEFhFAQeKtAAEIQAACFUPgkksusX322ccmT55cMWNmoBCAAAQgUFkEUJAq63oxWghA\nAAI1TeDTTz+1V1991ebOnVvTHJg8BCAAAQgUjwCJJIrHNq+WE4mE/fLLLzZlypS86jdWpV9/\n/dX326RJk8ZqknYagcCCBQtK/l5ohGFXbRMLFy40fUbnzZtXtXOstInpu0vy008/8VmJycXT\nZ0TXpdS/YzGZfiyHoe8uyaxZs2z27NmxHGMtDkqfk2nTphn3XuW5+rrHCj4b9Y0ABak+QkU+\nrg+JEh6uuOKKRe4pvfnp06dbq1atbOmll04/wF7ZCHz//ffWtGnTkr8XyjbhCuhYqxT6Ql12\n2WUrYLS1McSllkoaPihZbKm/N2uDcOGz1A3Hjz/+yPUoHF3RztB314wZM/zvvH7rkXgQ0Oek\nTZs2JLou0+XQgkTwG1LfEFCQ6iNUguNSknRjXEpRn3qTlLrfUs6xEvsqx3uhEjmVasy6HlyT\nUtHOrx9dDwnfX/nxKkUtPieloFxYH8FNIJ+TwrgVu3bwe8K9V7FJZ28/39UjnY0PUnaGlEIA\nAhCAAAQgAAEIQAACNUiAFaQYXPSJEyfa0KFDSzoSLb/LvI6nGCXFXmdnshXX0z7MIerEVNKD\ngb1y8+bNS9ovneUmoOh17dq1s9tuu81WWGGF3BU5UjIC8kGaM2cO310lI15/R/ru0u98ixYt\nMKWvH1fJauhzomsSrPCVrGM68gQKWUFq4r7YEnArHwF9WEaNGlXyAehNwge05Njr7PD+++/3\nvi59+vSpsx4HS0cg+HoMzLpK1zM95SLw3HPP2ddff2177723yQ8JiQcBflPicR2CUegz8sor\nr9hGG21k6667blDMa5kJ8Dkp8wVw3bdu3dq23377egeCglQvIipAoDQEevbsaV27drVHHnmk\nNB3SCwQqkMDf/vY3e+yxx+zZZ5+1Tp06VeAMGDIEik9AnxF9Vs444wzr169f8TukBwhUGQF8\nkKrsgjIdCEAAAhCAAAQgAAEIQKDhBFCQGs6OMyEAAQhAAAIQgAAEIACBKiOAglRlF5TpVC4B\n+VOQb6dyrx8jLw0BBTHRZ4UAM6XhTS+VSUCBZfQ5UUAABAIQKJwAPkiFM+MMCEAAAhCAAAQg\nAAEIQKBKCbCCVKUXlmlBAAIQgAAEIAABCEAAAoUTQEEqnBlnQAACEIAABCAAAQhAAAJVSgAF\nqUovLNOCAAQgAAEIQAACEIAABAongIJUODPOgEDRCYwePdreeeedovdDBxCoJAIzZ860J598\n0u677z6fLLaSxs5YIVBqApMmTfKflVL3S38QqAYCKEjVcBWZQ1URePfdd+3ss8+2jz/+uKrm\nxWQgsCQExo0bZ3vssYfdf//99uGHH1r//v1tzJgxS9Ik50KgagnMmjXLTj/9dBs1alTVzpGJ\nQaCYBJoVs3HahgAE8iewYMECu+OOO/xfkyZN8j+RmhCoAQIXXnih7b777jZw4EDT5+O2226z\nyy67zO6++26/XwMImCIE8iLw2muv2ZAhQ+ynn36y1VdfPa9zqAQBCKQTYAUpnQd7ECgbgccf\nf9wee+wxu+CCC6xz585lGwcdQyBuBKZOnWpjx471K0jBw4Ndd93VvvnmG1Za43axGE9ZCcgM\n9cwzz7SddtrJDjrooLKOhc4hUMkEUJAq+eox9qoi0Lt3b/80fPPNN6+qeTEZCCwpgcmTJ/sm\nVl111VRT7dq1MyXD/P7771NlbECg1gm0bNnS7r33XjvyyCOtWTOMhGr9/cD8G06AT0/D2XEm\nBBqVgG74EAhAIJPAt99+ay1atPB/4aNt2rSxH3/8MVzENgRqmoCUIn5LavotwOQbiQAKUiOB\npBkI5Etg2rRp9tRTT6Wqd+jQwbbddtvUPhsQgEA6gaWXXtrkoxeVX3/91Vq1ahUtZh8CEIAA\nBCCwRARQkJYIHydDoHAC06dPt0ceeSR1Yvfu3VGQUjTYgEAmgZVWWsmkDM2ePTtNIZoxY4at\nssoqmSdQAgEIQAACEFgCAihISwCPUyHQEAKKKjR8+PCGnMo5EKhJAp06dfL+FB999JH16tXL\nM1DQhoULF1rYL6km4TBpCEAAAhBodAIEaWh0pDQIAQhAAAKNSaBt27a2ww472C233GLK7zJ3\n7ly78cYbrU+fPta+ffvG7Iq2IAABCEAAAoaCxJsAAhCAAARiT+CYY47xUet2220323PPPf2K\n0oABA2I/bgYIAQhAAAKVR6BJwknlDZsRQwACEIBALRKQ31HTpk2tdevWtTh95gwBCEAAAiUg\ngIJUAsh0AQEIQAACEIAABCAAAQhUBgFM7CrjOjFKCEAAAhCAAAQgAAEIQKAEBFCQSgCZLiAA\nAQhAAAIQgAAEIACByiCAglQZ14lRQgACEIAABCAAAQhAAAIlIICCVALIdAEBCEAAAhCAAAQg\nAAEIVAYBFKTKuE6MEgIQgAAEIAABCEAAAhAoAQEUpBJApgsIQAACEIAABCAAAQhAoDIIoCBV\nxnVilBCAAAQgAAEIQAACEIBACQigIJUAMl1AAAIQgAAEIAABCEAAApVBAAWpMq4To4QABCAA\nAQhAAAIQgAAESkAABakEkOkCAhCAAAQgAAEIQAACEKgMAihIlXGdGCUEIAABCEAAAhCAAAQg\nUAICKEglgEwXEIAABCAAAQhAAAIQgEBlEEBBqozrxCghAAEIQAACEIAABCAAgRIQQEEqAWS6\ngAAEIAABCEAAAhCAAAQqgwAKUmVcJ0YJAQhAAAIQgAAEIAABCJSAAApSCSDTBQQgAAEIQAAC\nEIAABCBQGQRQkCrjOjFKCEAAAhCAAAQgAAEIQKAEBFCQSgCZLiAAAQhAAAIQgAAEIACByiCA\nglQZ14lRQgACEIAABCAAAQhAAAIlIICCVALIdAEBCEAAAhCAAAQgAAEIVAYBFKTKuE6MEgIQ\ngAAEIAABCEAAAhAoAQEUpBJApgsIQAACEIAABCAAAQhAoDIIoCBVxnVilBCAAAQgAAEIQAAC\nEIBACQigIJUAMl1AAAIQgAAEIAABCEAAApVBAAWpMq4To4QABCAAAQhAAAIQgAAESkAABakE\nkOkCAhCAAAQgAAEIQAACEKgMAs0qY5iMEgIQgED1Evjf//5nb775Zr0T3GKLLWzllVeut16l\nVZg9e7Z98MEHNmHCBFtttdVs/fXXt7Zt2zbKNCZOnGjvvPOOtW7d2jbbbDP/WkjDM2fOtLff\nftt+/PFHf/4qq6yS1+njx4+3l19+2Q455JCc9b/66iv75JNP7JdffrHu3bvbuuuum7Pu119/\n7RmpwgYbbGBdunTJWTfXgSeffNI+/fRTGzhwYK4q9tBDD9naa69t6623XkadGTNmeA4ZB1yB\n+K600krZDmWUab663pr/6quvbhtttJEttVTm89rvv//e7rvvPps2bZrtsMMOnn+0MV2fc845\nxw477DDbcMMN0w5PnTrVzj//fDvjjDOsQ4cOacfYgQAEIFAngQQCAQhAAAJlJXDnnXcm3Bd1\nvX+PPvpoUcfpbloTBx98cFH7iDZ+2223JdzNa9rc27Rpk7jiiiuiVQveP/vssxPNmjVLtd20\nadPExRdfnHc7w4cPT7ib/tT5ukZOSU189913dbYxffr0RI8ePRLLLrts1nrffvttYo899khr\nV21vs802iS+//DLtnLlz5yaOOOKIRJMmTVL1tX3UUUcl5syZk1a3rh2NuV27dol77rknZ7Xr\nr7/e93HJJZdkrXPsscemxhB9vx500EFZz4kW6j28/PLLp7Wz8cYbJz777LO0qk4pSnTt2jWh\n98Jvf/vbhFOgEhpfVP7xj38knNKacEp29JDf33333RP7779/1mMUQgACEMhFwHIdoBwCEIAA\nBEpDIFCQdt5558Stt96a88+tNBV1QGuttVaiU6dORe0j3PhTTz3lb/y7deuWuOCCCxJS0KQY\nuZUUfwN9++23h6sXtK22dRO/1157JdwKUOK1115L7Ljjjr7s3//+d71tvfjiiwkpVGKiG3ON\n7dxzz00ss8wyvkyKSzbRjX3QTzYF6ddff0388Y9/9OPQjfvjjz+eeOGFFxL9+/f3LNzKTZri\nc+KJJ/q6O+20U0JzeuaZZxJ6n2huAwYMyDaErGXqa5NNNsl6TIVu5Six9NJL+3ZzKUhSDjUn\njSn6d8cdd+RsOzjwyCOP+Dm6FcLEiBEj/HU55phjPGeVzZ8/P6ia0GfCrUolpExK/vznP3vF\n6ueff07VEWu30pi48sorU2XRjY8//tgrV5ofAgEIQCBfAihI+ZKiHgQgAIEiEQgUpNNOO61I\nPeTXbKkVpK233trfkI8aNSptgK+//rov/81vfpNWnu+ObqKldDlzvcSCBQtSp82bN8+XSwkM\nl6cqhDZ22WUXP4aRI0eGShOJfv36+XIpK1HRTb9WM6S8NG/ePOsKkpQhHZeyEZVA8bn33nv9\noYULF/oVFCklP/30U6q6M3Xz5VLWnLlaqjzXhhRE9enM1TKq/PDDDwlnBuiPt2jRwr9mU5Ck\n2Elh0TVrqEhB04pQdLVIypvG9/zzz6eaPvDAAxO///3vU/tScFTn3XffTZWdfvrpfpVJ17Uu\n2XPPPf2KnngiEIAABPIhkGn0676BEAhAAAIQiD8B+bhcddVV9te//tX++c9/mjOfMreykXXg\nTiGwMWPG2IUXXmhOEbNhw4Z53xdVlm+JM3Xzr0658NujR49Oa+ejjz6yyy+/3PflVmDM3aim\nHdfOc889Zw888IC5lQC79tprbfDgwfbhhx9m1FOBu1k19eWUINtuu+3S6vTq1cv748hfxt2Y\np465G2g/Nvls1SVu9cfkA9S3b19zq0Cpqk5pMWdCaPJLkj9OXeJM4OzUU081p7SkVdt22239\n/tixY9PKn3jiCdt777393B9++OGsPjw6QeNyypu5FaO087Vz6KGH+jK36uFfxUf+WfIJCvtk\nOSXD+9voWss/pz5xCo85Jcuc0pdRVfPTe2G//fYzt1KWcTwo+Pzzz/31ckpOUFTQq66J/OzO\nPPNMP5/wyRqfWxnz74WgXP5J8msKxCmDflPvVYkzGbT//Oc/5swoTde1LjnggANM18ut1tVV\njWMQgAAEFhPIR4uiDgQgAAEIFI9AoStIWk1wN7T+ibr8UcJ+Muuss05i0qRJaYN1AQYSMmFy\n3/ypFQlty09Gfix6oh/1cdET/ECcAubNoFRHKyR6lU+IysMrGLvuumvCBQ9IHH/88b4v9fF/\n//d/QTN5v2pMyy23XGLNNddMO0f+JGrTKSBp5dEdmcKpnlPWooe8KZmOqU6hohUImezpfKf4\npZ2uFaW///3vCRcYwJe7wANZV5DSTorsOIXStx02V9Mqivp77733UrW/+OILz79nz56pslwb\neq/IDyt8PcN15Vf09NNP+yJxVV/ZVpDuvvtuf+yuu+5KOMU8ITNFmYO6IBPh5nJuX3rppf78\nt956y9fRuP773/8mXCCGrOc4pSbhFMPUMfcgwJ8fvLf/8pe/+OPh91+qcmTDBXLwppHy+0Ig\nAAEI5EMAE7t8KFEHAhCAQBEJBAqSzLdkDpXtTzd5gbioXf5m0UUjS0yZMsUXy9di33339eXu\nKX1QNSFfmT/84Q8JmU/pxls3+XJov+iii3xdF+UrVTebid1NN93k68mvZvLkyb6u+txtt918\nefhmWgqS/HbkhH/DDTckFORAvjyFSqDguBWctFPdClbCRSvzfNIORHaCYAIyZ4uKWxnz41aQ\ng3zFrZ4lBg0alJDSI8XwX//6V72nFqogiakUXSmGgd+NOnn//fe9ctuyZUtvCidfJZncSXmU\nKWJ9ImVGSs91111XX1WveOZSkGTOpmNSWvQa/GVTlLN1JGVa57iVoYTeJzovaMOtvCVk6hcW\n+VrpuHyUpIjJLDJQcFxEP/9+ditf4VPq3N5qq628OV6dlTgIAQhAYBEBFCTeChCAAATKTCBQ\nkIIbxmyvYf8MKUbbb799Qr42YXEmTP6mcp999kkVB8EK5FQfFilKzlzMtxM4x0cVJNWRsrPi\niium+cConVmzZiVcyHF/s65tiW58NXZn+uT3G/JPUdZ086wb8VyRyeprN/Cpia7y6DyVaYyF\nROuTMhVcEzGS0lKfFKIgiZ8LQe77uPHGG9Oalu+PFLKg/+BVSrKO1SdSjHSOMwGsr2qdClIQ\neELKtgJLKGCIXhVUQu07E8862w/8jMRFUek0T61KBdH8ttxyS6+8hxuRku3CgPv3oK6pgjJI\ndD20Ihqef3g73Eaw7cwt/cqn/LcQCEAAAvURIA+S+2ZHIAABCMSBgDOnMqf4ZB2K/FYCkS9Q\nWNzTd59PRz5AEvmtBKIcQBL5x4TFmcnZs88+Gy7K2FZeImcK5X1jwj4wqij/EGduZtdcc43v\n24VqTp2vfEMNEbdSYEcffbS1b9/e5MfjVk0a0owF/ipOwcs4391I+7Kwb1JGpUiB/Fzk46Ux\nye/ld7/7nff90liXVHTtnOmguSh75szGzIX0TjUpXy4XFMGcWZoNHTo0lVPJrcyZW9Ext0Jm\njz32WJqvTurkRRvyHZN07tx5UUnDXs466yxzSo734Qr4ulUdn8NIOZyUb0i+cGG/oXBPge+Q\n/KbcCmnqGsk/yK3u2EsvvWQuOIVpP5AjjzzS9BcWZ15ot9xyi6/rFGmTX9pxxx1nKld+KL0f\ns73/lDfK3RCZ/LuyHQ/3wTYEIAABFCTeAxCAAARiQqB3797e6by+4ejG35nLmRQKJdxUQkzJ\nCius4F91IxiI813xmw25QVaQBEnXrl39a/RfUK6b07CCpOSfhYrLZ+MTfupcBVBwvlSFNpGq\nv+qqq/rtbAEMgrKowpc6OcuGFAGJFCJdI7d64RWlJVWQXM4j69Onj7+5lwIiJSMsuvl/9dVX\nzZkceuUjOOZWA32ADQWRcCuEXlENjkVfg4APwRyix/PddytHpr+oKHGxlPr777/fKx8KsJFN\nggS7zj8tpRwF9Zx/lFeQNNewghQcD7+KhRLCSjmXsutWS02BI9wqm1ciFXRCXN3KZ/g0C+aP\ngpSGhR0IQCAHgaVylFMMAQhAAAIxJXDCCSeY81cy54vhn+rffPPNfpUhuBkOD9vltvG74VWl\n8PG6toPVAEVTyybOL8oXBysKQZ36oooF9fQqZc6ZDHrlSDfXukleEuVIbeajILkQ4KpasDiT\nMr8Coeh84t9Q0flSOBTVTtHjosqR2nUhxn3zLkx1RjfO38yXucSrGcfCBVplkWglsFiiFT9J\nsEqUrZ9AQenYsWPGYRfIw5c5P6yMY+ECrYa5IBF+NU/liuLoApCY3v/OvNOcv5yP6vfggw+G\nT/PbwfwLWTnMaIQCCECgZgigINXMpWaiEIBANRBwUb+8GZHCY+sm++qrr7bDDz/cm33pybkk\nMCPTtvOZ0Yt/qu43Qv+GDBniTe8UUjmbKLy0JJviFS4PVpJ85QL+aSVM4a4VNlxKgEzGst1A\nF9Ckr+qi8/lXhZaOSlC26aabRg+l9p1PkOcWhPROHVi0ESgdCp3dEFG4a5cs1tSPTOScT03W\nZoJ+dM2jIvM7SfhaR+toP1i5cdHmsh3Oq0yKsFYInZ+QD88ePSlo2yX4jR5K7QfXROZ1UXFB\nKXxRrtWnoL4LlOHHoFU3iUKD6wFAoHzpfSjT0XHjxgWnpF6DMQY8UgfYgAAEIJCFAApSFigU\nQQACEIgrgeDmT4pE2EdHKzHyv5C40Mep4cvkSDeN8p0Ji572K0+RbjKD1RTdbIZXi9TH5ptv\n7s24dFMfFilnjzzyiMkkzoWbDh/Ke9sFELBbnZmgzKVkotWqVau8z62ropQP+aMoL1R4VWP6\n9Om+TCZa8nvJJVJ8ZIInZSrw4QrqaoVL/kJqwwWvCIrzfnUhzH3OIXF2CXJthx12yHmufNIk\n4hT1p3IBDPyxoI7fyfJvjTXW8KWBuWSWKvUWKe+SFDLNXdcpLFrFkWIrZTJQVMLHg22ZwsnM\nU/m2XKjuoNi/Xnnllf41mwlfUFHvP60MhVfa9H5Rfq/g/S6m+hxEzevURqAgBTyCdnmFAAQg\nkJWA+zJBIAABCECgjASCKHYugWu9o3A3gQln0uQjhzm/lcQrr7zio4G5FZiEu2H0+V4UJSws\nzvHf11ceIeW6cUlcE85vw5ddccUVqapOsfBlCjeu8N4SRcZzilPCKQw+P47CLyvctiLb6c8l\njE2dH0Sxc4pIqizXhsI6K0Ke+2Hy0fQUzSzbXzi8eb55kNSnQoyrbRdQIXHfffclXAAAH6Zb\nYciDXDzB2ILcRiNGjAiKEi5ogM8fJNYKN655uxU3H4bbmRDWG2o8VxQ7hQvXuJwZYNb5ioGi\nt0mcUpRwCpSvr7DqivqmaHTB9dxiiy0STkFIjTnbhkKBqz+FPq9P6sqDpPm7Fa1Eu3btEn/7\n29987qSLL77YRzHU+yCcp0nb6jP6PnTKsI8kp/xbTplPOAXRRxNU3ZNPPrnO4SmKXjSnlgtK\n4vvR9ZUojL3acopcRlt6/4bzKmVUoAACEIBAiABhvkMw2IQABCBQDgKFKEgan27eFW5aN4P6\n002/lBO3upTKMRMk1FR93UQrDLPzKUqdI+VEyT7D4lYCEh06dPB1FL45EOVlciZWqXOVk2e7\n7bbLUDQKUZAeeuihVHvBPLK9BqGdNZZCFCTVF1cXuCLVj7ajYbRVL5uCpHIlUHVmY6nzNT63\nopamFKpeNsmlILmVp7T2ss1ZSVADUQhwKQ9SyoK6Ulhd5LaM0OvBOeFXKVlK7qtx1yd1KUg6\n15kDpuVB0vtOiWyV2ygsuRSkoA0lEw7morGdcsopGSG+w+0FuavGjBkTLvbbSpisxMVKmqs2\ns+W30vh07KSTTso4nwIIQAAC2Qg0UaH74kAgAAEIQKCCCMjkSkECZEKmoAbRQAnZpqJz5G8k\nvxWXaNSaNWuWrZp999133sQs2qb6UlABhXUuJBBD1k5KVKifOPlmzZs3z/sVuYS5Bfcsk7Bv\nvvnG5JOVzXyr4AYbcIJMyRQtUNdQ45A5ZL6iEOFOObA33njDR3zL97xc9eQzpD+9DxpqFumS\nDvvAEWqjPnErRL4/hUGPiq6vwq+PHTvWhxwP/JPC9dyKVyocfUP95cLtsQ0BCFQ/ARSk6r/G\nzBACEIAABGqYgHx0FH3Pmbxl+BBVOxaFdVcOJIVGD/svVfu8mR8EILBkBAjSsGT8OBsCEIAA\nBCAQawJabbr00kt9kIPPPvss1mNt7MFdddVVttxyy/nEuo3dNu1BAALVS4AVpOq9tswMAhCA\nAAQgkCKgiHkyMQsi4KUOVOmGcn9pvkoiq7xhCAQgAIF8CaAg5UuKehCAAAQgAIEKJuAiB/oQ\n2w0Ny15pU1eeKfkmuYiNPtR9pY2f8UIAAuUjgIJUPvb0DAEIQAACEIAABCAAAQjEjAA+SDG7\nIAwHAhCAAAQgAAEIQAACECgfARSk8rGnZwhAAAIQgAAEIAABCEAgZgRQkGJ2QRgOBCAAAQhA\nAAIQgAAEIFA+AihI5WNPzxCAAAQgAAEIQAACEIBAzAigIMXsgjAcCEAAAhCAAAQgAAEIQKB8\nBFCQyseeniEAAQhAAAIQgAAEIACBmBFAQYrZBWE4EIAABCAAAQhAAAIQgED5CKAglY89PUMA\nAhCAAAQgAAEIQAACMSOAghSzC8JwIAABCEAAAhCAAAQgAIHyEUBBKh97eoYABCAAAQhAAAIQ\ngAAEYkYABSlmF4ThQAACEIAABCAAAQhAAALlI4CCVD729AwBCEAAAhCAAAQgAAEIxIwAClLM\nLgjDgQAEIAABCEAAAhCAAATKRwAFqXzs6RkCEIAABCAAAQhAAAIQiBkBFKSYXRCGAwEIQAAC\nEIAABCAAAQiUjwAKUvnY0zMEIAABCEAAAhCAAAQgEDMCKEgxuyAMBwIQgAAEIAABCEAAAhAo\nHwEUpPKxp2cIQAACEIAABCAAAQhAIGYEUJBidkEYDgQgAAEIQAACEIAABCBQPgIoSOVjT88Q\ngAAEIAABCEAAAhCAQMwIoCDF7IIwHAhAAAIQgAAEIAABCECgfARQkMrHnp4hAAEIQAACEIAA\nBCAAgZgRQEGK2QVhOBCAAAQgAAEIQAACEIBA+QigIJWPPT1DAAIQgAAEIAABCEAAAjEjgIIU\nswvCcCAAAQhAAAIQgAAEIACB8hFAQSofe3qGAAQgAAEIQAACEIAABGJGAAUpZheE4UAAAhCA\nAAQgAAEIQAAC5SOAglQ+9vQMAQhAAAIQgAAEIAABCMSMAApSzC4Iw4EABCAAAQhAAAIQgAAE\nykfg/wE4IByGC3ET2AAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plot(acm,2,3,roweti=sel,main=\"Representación simultanea factores 2-3\",gg=TRUE)\n",
"t(Y[sel,])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Razones de correlación sobre un eje de las variables cualitativas\n",
"\n",
"- Una variable cualitativa induce una partición de los $n$ individuos y la inercia (varianza) de los individuos sobre el eje se puede descomponer en $varianza \\ inter + varianza \\ intra$. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<center>\n",
"<img src=\"data:image/png;base64,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\" alt=\"Varianza inter e intra\" width=\"600\" height=\"500\">\n",
"<center>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "59Z-jc8fUX85"
},
"source": [
"- La razón de correlación se define como el cociente entre varianza inter y varianza total. \n",
"- La varianza total de $F_s$ es $\\lambda_s$, \n",
"- La varianza inter con respecto a una variable $q$ es:\n",
"$$\n",
" \\sum_{j \\in J_q} \\frac{n_j}{n} (\\overline{F}_{sj})^2\n",
"$$\n",
" puesto que las coordenadas sobre $s$ están centradas.\n",
"donde $\\overline{F}_{sj} = \\sum\\limits_{i \\in I_{j \\in J_q}} \\frac{1}{n_j} F_{s}(i)$, es decir, el promedio aritmético de las coordenadas sobre el eje $s$ de los individuos que asumen la categoría $j$ de la variable $q$. \n",
"- Por las relaciones de transición $\\overline{F}_{sj} = \\sqrt{\\lambda_s} G_s(j)$, entonces:\n",
"$$\n",
"Varianza \\ entre (q) = \\lambda_s \\ \\sum_{i \\in J_q} \\frac{n_j}{n} G_s^2(j)\n",
"$$\n",
"y la razón de correlación es:\n",
"$$\n",
"\\eta^2_s(q) = \\sum_{j \\in J_q} \\frac{n_j}{n} G_s^2(j) \n",
"$$\n",
"- Se puede expresar como función de la contribución absoluta de las categorías como:\n",
"$$\n",
"\\eta^2_s(q) = \\lambda_s s \\sum_{j \\in q_j} Ca_s(j) \n",
"$$\n",
"donde $J_q$ es el conjunto de categorías de la variable $q$ y $Ca_s(j)$ es la contribución absoluta de la categoría $j$ sobre el eje $s$. \n",
"- Estos valores se encuentran en el objeto de salida de la función *dudi.acm{ade4}*, en la tabla *cr*.\n",
"- Con estas razones de correlación se pueden obtener los planos factoriales para las variables cualitativas. \n",
"- Por ejemplo para la variable $Origen$, la suma de las contribuciones de las tres categorías sobre el primer eje es $13.45+4.87+27.18=45.5\\%$, el primer valor propio es $0.3366$ y el número de variables $4$, \n",
"- La razón de correlación es $\\eta^2_1(Origen)=4*0.3366*0.455=0.613$, valor que se puede leer en la figura siguiente.\n"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"id": "aX6bvWJxUX85",
"outputId": "0ec2e20a-2463-445e-ebc4-8a2dafdce2b2"
},
"outputs": [
{
"data": {
"image/png": 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3mvTr6WND+c1ut3kmrND4LvPTg66b+T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\nYII=",
"text/plain": [
"Plot with title “Factores 1-2, razones de correlación”"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plotfp(acm$cr,main=\"Factores 1-2, razones de correlación\") # función de FactoClass"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"id": "Sm4NrmboUX85",
"outputId": "431b3fcf-2714-405a-d853-8b3993e5feba"
},
"outputs": [
{
"data": {
"image/png": 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fnlKTDqU1N1/lzfqx/6tq1iYRg72P6tX93iu7PtnZFrkm39xv/5mac+mvf5pFFt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\nIRf4/54r+yzEi1rFAAAAAElFTkSuQmCC",
"text/plain": [
"Plot with title “Factores 2-3, razones de correlación”"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plotfp(acm$cr,2,3,main=\"Factores 2-3, razones de correlación\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "hP_6uHlWUX85"
},
"source": [
"# **Elementos suplementarios**\n",
"\n",
"## Individuos suplementarios\n",
"\n",
"- Los individuos ilustrativos se pueden proyectar utilizando la fórmula cuasibaricéntrica.\n",
"- La coordenada de un individuo suplementario es el promedio de las coordenadas de las categorías que asume, dilatado por el inverso de la raíz cuadrada del valor propio.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "V8m6DpmgUX85"
},
"source": [
"## Variables cualitativas suplementarias\n",
"\n",
"- Las categorías de una variable ilustrativa se proyectan mediante la fórmula cuasibaricéntrica \n",
" - Como el promedio de las coordenadas de los individuos que la asumen, dilatado por el inverso de la raíz cuadrada del valor propio. \n",
" - Se pueden calcular sus cosenos cuadrados sobre los ejes.\n",
" - Valores test.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "GbfyaCIAUX86"
},
"source": [
"### Valores test para categorías suplementarias\n",
"\n",
"- Una categoría $j$ es asumida por los $n_j$ individuos del conjunto $I_j$, \n",
"- Su coordenada, sobre un eje $s$ es el promedio aritmético de las coordenadas de esos individuos sobre el eje, multiplicada por el inverso de la raíz cuadrada del valor propio $\\lambda_s$. \n",
"- Si se supone que los $n_j$ individuos se extraen al azar de los $n$ individuos:\n",
" - La media de las coordenadas es 0 y su varianza es $\\left( \\dfrac{n-n_j}{n-1} \\right) \\dfrac{\\lambda_s}{n_j}$. \n",
" - La varianza de la categoría $j$ se obtiene multiplicando la varianza anterior por $\\dfrac{1}{\\lambda_s}$: \n",
" $$\\dfrac{1}{\\lambda_s} \\left( \\dfrac{n-n_j}{n-1} \\right) \\dfrac{\\lambda_s}{n_j} = \\dfrac{n-n_j}{n(n-1)} $$\n",
" - El valor calculado de la estadística $T$ para la verdadera coordenada es:\n",
" $$\n",
" t_s(j) = \\sqrt{\\dfrac{n_j(n-1)}{n-n_j}} G_s(j)\n",
" $$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "B7QK9enhUX86"
},
"source": [
"#### Ejemplo: alor test para *Química* sobre el primer eje:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"id": "t9QnY2HSUX86",
"outputId": "e12e5573-7751-4228-df6d-5b3a09c33a90"
},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 1 × 7 of type int</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>Biol</th><th scope=col>Esta</th><th scope=col>Farm</th><th scope=col>Fisi</th><th scope=col>Geol</th><th scope=col>Mate</th><th scope=col>Quim</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>nCarr</th><td>63</td><td>66</td><td>73</td><td>82</td><td>45</td><td>53</td><td>63</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 1 × 7 of type int\n",
"\\begin{tabular}{r|lllllll}\n",
" & Biol & Esta & Farm & Fisi & Geol & Mate & Quim\\\\\n",
"\\hline\n",
"\tnCarr & 63 & 66 & 73 & 82 & 45 & 53 & 63\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 1 × 7 of type int\n",
"\n",
"| <!--/--> | Biol | Esta | Farm | Fisi | Geol | Mate | Quim |\n",
"|---|---|---|---|---|---|---|---|\n",
"| nCarr | 63 | 66 | 73 | 82 | 45 | 53 | 63 |\n",
"\n"
],
"text/plain": [
" Biol Esta Farm Fisi Geol Mate Quim\n",
"nCarr 63 66 73 82 45 53 63 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Valor test de química: -2.216"
]
}
],
"source": [
"# Número de admitidos por carreras:\n",
"t(data.frame(nCarr=summary(admi$carr)))\n",
"# Valor test:\n",
"vtQui = sqrt(63*(445-1)/(445-63))*(-0.259)\n",
"cat(\"Valor test de química:\",round(vtQui,3))\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "xZwjBvQ6UX86"
},
"source": [
"- La diferencia con el valor de la salida se debe al número de cifras significativas. \n",
"- Este valor, menor que -2, indica que es válido leer la posición negativa de Química sobre el primer eje, lo que significa que está asociada con estrato bajo y origen fuera de Bogotá.\n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "XJJ6Z60sUX86"
},
"source": [
" #### Carreras sobre el primer plano factorial del ACM de admitidos"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"id": "XussnlZZUX86",
"outputId": "68045f6e-4c0f-4887-dd94-1e8bbef9d0c1"
},
"outputs": [],
"source": [
"supCarr<-supqual(acm,admi$carr)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"id": "0yRmy13oUX87",
"outputId": "50fe8ff4-99a3-4927-8373-fb4906612484"
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Coordenadas y ayudas para la interpretación"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 7 × 11 of type dbl</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>ncat</th><th scope=col>dis2</th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Axis3</th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Axis3</th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Axis3</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>qual.Biol</th><td>63</td><td>6.063</td><td>-0.018</td><td> 0.146</td><td> 0.068</td><td>-0.156</td><td> 1.245</td><td> 0.579</td><td>0.000</td><td>0.003</td><td>0.001</td></tr>\n",
"\t<tr><th scope=row>qual.Esta</th><td>66</td><td>5.742</td><td> 0.029</td><td>-0.104</td><td> 0.018</td><td> 0.255</td><td>-0.912</td><td> 0.160</td><td>0.000</td><td>0.002</td><td>0.000</td></tr>\n",
"\t<tr><th scope=row>qual.Farm</th><td>73</td><td>5.096</td><td> 0.168</td><td> 0.198</td><td>-0.392</td><td> 1.566</td><td> 1.845</td><td>-3.664</td><td>0.006</td><td>0.008</td><td>0.030</td></tr>\n",
"\t<tr><th scope=row>qual.Fisi</th><td>82</td><td>4.427</td><td> 0.095</td><td>-0.029</td><td> 0.127</td><td> 0.948</td><td>-0.292</td><td> 1.267</td><td>0.002</td><td>0.000</td><td>0.004</td></tr>\n",
"\t<tr><th scope=row>qual.Geol</th><td>45</td><td>8.889</td><td>-0.040</td><td> 0.076</td><td> 0.635</td><td>-0.284</td><td> 0.540</td><td> 4.490</td><td>0.000</td><td>0.001</td><td>0.045</td></tr>\n",
"\t<tr><th scope=row>qual.Mate</th><td>53</td><td>7.396</td><td>-0.050</td><td>-0.462</td><td>-0.112</td><td>-0.387</td><td>-3.579</td><td>-0.869</td><td>0.000</td><td>0.029</td><td>0.002</td></tr>\n",
"\t<tr><th scope=row>qual.Quim</th><td>63</td><td>6.063</td><td>-0.259</td><td> 0.106</td><td>-0.156</td><td>-2.217</td><td> 0.907</td><td>-1.335</td><td>0.011</td><td>0.002</td><td>0.004</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 7 × 11 of type dbl\n",
"\\begin{tabular}{r|lllllllllll}\n",
" & ncat & dis2 & Axis1 & Axis2 & Axis3 & Axis1 & Axis2 & Axis3 & Axis1 & Axis2 & Axis3\\\\\n",
"\\hline\n",
"\tqual.Biol & 63 & 6.063 & -0.018 & 0.146 & 0.068 & -0.156 & 1.245 & 0.579 & 0.000 & 0.003 & 0.001\\\\\n",
"\tqual.Esta & 66 & 5.742 & 0.029 & -0.104 & 0.018 & 0.255 & -0.912 & 0.160 & 0.000 & 0.002 & 0.000\\\\\n",
"\tqual.Farm & 73 & 5.096 & 0.168 & 0.198 & -0.392 & 1.566 & 1.845 & -3.664 & 0.006 & 0.008 & 0.030\\\\\n",
"\tqual.Fisi & 82 & 4.427 & 0.095 & -0.029 & 0.127 & 0.948 & -0.292 & 1.267 & 0.002 & 0.000 & 0.004\\\\\n",
"\tqual.Geol & 45 & 8.889 & -0.040 & 0.076 & 0.635 & -0.284 & 0.540 & 4.490 & 0.000 & 0.001 & 0.045\\\\\n",
"\tqual.Mate & 53 & 7.396 & -0.050 & -0.462 & -0.112 & -0.387 & -3.579 & -0.869 & 0.000 & 0.029 & 0.002\\\\\n",
"\tqual.Quim & 63 & 6.063 & -0.259 & 0.106 & -0.156 & -2.217 & 0.907 & -1.335 & 0.011 & 0.002 & 0.004\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 7 × 11 of type dbl\n",
"\n",
"| <!--/--> | ncat | dis2 | Axis1 | Axis2 | Axis3 | Axis1 | Axis2 | Axis3 | Axis1 | Axis2 | Axis3 |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| qual.Biol | 63 | 6.063 | -0.018 | 0.146 | 0.068 | -0.156 | 1.245 | 0.579 | 0.000 | 0.003 | 0.001 |\n",
"| qual.Esta | 66 | 5.742 | 0.029 | -0.104 | 0.018 | 0.255 | -0.912 | 0.160 | 0.000 | 0.002 | 0.000 |\n",
"| qual.Farm | 73 | 5.096 | 0.168 | 0.198 | -0.392 | 1.566 | 1.845 | -3.664 | 0.006 | 0.008 | 0.030 |\n",
"| qual.Fisi | 82 | 4.427 | 0.095 | -0.029 | 0.127 | 0.948 | -0.292 | 1.267 | 0.002 | 0.000 | 0.004 |\n",
"| qual.Geol | 45 | 8.889 | -0.040 | 0.076 | 0.635 | -0.284 | 0.540 | 4.490 | 0.000 | 0.001 | 0.045 |\n",
"| qual.Mate | 53 | 7.396 | -0.050 | -0.462 | -0.112 | -0.387 | -3.579 | -0.869 | 0.000 | 0.029 | 0.002 |\n",
"| qual.Quim | 63 | 6.063 | -0.259 | 0.106 | -0.156 | -2.217 | 0.907 | -1.335 | 0.011 | 0.002 | 0.004 |\n",
"\n"
],
"text/plain": [
" ncat dis2 Axis1 Axis2 Axis3 Axis1 Axis2 Axis3 Axis1 Axis2\n",
"qual.Biol 63 6.063 -0.018 0.146 0.068 -0.156 1.245 0.579 0.000 0.003\n",
"qual.Esta 66 5.742 0.029 -0.104 0.018 0.255 -0.912 0.160 0.000 0.002\n",
"qual.Farm 73 5.096 0.168 0.198 -0.392 1.566 1.845 -3.664 0.006 0.008\n",
"qual.Fisi 82 4.427 0.095 -0.029 0.127 0.948 -0.292 1.267 0.002 0.000\n",
"qual.Geol 45 8.889 -0.040 0.076 0.635 -0.284 0.540 4.490 0.000 0.001\n",
"qual.Mate 53 7.396 -0.050 -0.462 -0.112 -0.387 -3.579 -0.869 0.000 0.029\n",
"qual.Quim 63 6.063 -0.259 0.106 -0.156 -2.217 0.907 -1.335 0.011 0.002\n",
" Axis3\n",
"qual.Biol 0.001\n",
"qual.Esta 0.000\n",
"qual.Farm 0.030\n",
"qual.Fisi 0.004\n",
"qual.Geol 0.045\n",
"qual.Mate 0.002\n",
"qual.Quim 0.004"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Razones de correlación\n"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A matrix: 1 × 3 of type dbl</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Axis3</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>qual</th><td>1.64</td><td>3.88</td><td>7.47</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A matrix: 1 × 3 of type dbl\n",
"\\begin{tabular}{r|lll}\n",
" & Axis1 & Axis2 & Axis3\\\\\n",
"\\hline\n",
"\tqual & 1.64 & 3.88 & 7.47\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 1 × 3 of type dbl\n",
"\n",
"| <!--/--> | Axis1 | Axis2 | Axis3 |\n",
"|---|---|---|---|\n",
"| qual | 1.64 | 3.88 | 7.47 |\n",
"\n"
],
"text/plain": [
" Axis1 Axis2 Axis3\n",
"qual 1.64 3.88 7.47 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"attach(supCarr)\n",
"cat(\"\\nCoordenadas y ayudas para la interpretación\")\n",
"cbind(ncat,round(cbind(dis2,coor,tv,cos2),3))\n",
"cat(\"\\nRazones de correlación\\n\")\n",
"round(scr*100,2)\n",
"detach(supCarr)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "O_eHGCjGUX87"
},
"source": [
"- Sólo es legítimo interpretar como diferente de cero las coordenadas de: \n",
"- Química (-) sobre el primer eje, Matemáticas (+) sobre el segundo eje; y Geología (-) opuesto a Farmacia (+) sobre el tercer eje. \n",
" - Química tiene, en comparación al promedio, mayor proporción de admitidos de estrato bajo y origen fuera de Bogotá,\n",
" - Matemáticas de 19 o más años, \n",
" - Geología de 17 años y de estrato alto, \n",
" - Farmacia de 18 años y género femenino. \n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "yPPE6-dJUX87"
},
"source": [
"#### Proyección de las carreras sobre el primer plano factorial"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"id": "OmkaC80IUX87",
"outputId": "25d9b729-73c9-4369-e815-ed005bbaf182"
},
"outputs": [
{
"data": {
"image/png": 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KJnjr6jtu2cA+3LqiZ4nhcIhUKBrKo0lUUAAQRyXIAEKcc7mOYhgAACMQLTtHxo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\nekFgxowZy/TLsj1fQvG/wFdVxQcV1yjWKuYo7lJcqLByr+JKxcU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ekeiEz2MLX9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\n48onqWXpFyua3lYyi6P0+s7Xg9wwTRyfSOg7kP5XHHVts+we9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zAUaQfHZB6A4C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\ngwMAAAAASUVORK5CYII=",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plot(acm,Trow =FALSE,infaxes=\"no\",main=\"Plano 1-2\",\n",
"ylim =c( -1.5 ,1.3) , col.col=\" black \")\n",
"points( supCarr$coor ,col =\"darkgreen\")\n",
"text(supCarr$coor , labels = attributes (admi[,1])$levels ,\n",
"col =\"darkgreen\",pos =1, cex =0.8 , font =3)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "se-OFjYKUX87"
},
"source": [
"#### Proyección de las carreras sobre el plano factorial 2-3"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"id": "cx8Pa7DxUX87",
"outputId": "63413751-c6d4-4c18-ddd2-aae148f7e11f"
},
"outputs": [
{
"data": {
"image/png": 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UYUBBBAAAEE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vbVXzjj7j3HP2tKkHH3zw+/vtt5/dACHa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\n/bNES21EyIoi+8GwS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wGshqIauJnA3T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",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plot(acm,2,3,Trow =FALSE,infaxes=\"no\",main=\"Plano 2-3\",\n",
"ylim =c( -1.5 ,1.3) , col.col=\" black \")\n",
"points(supCarr$coor[,c(2,3)] ,col =\"darkgreen\")\n",
"text(supCarr$coor[,c(2,3)] , labels = attributes (admi[,1])$levels ,\n",
"col =\"darkgreen\",pos =1, cex =0.8 , font =3)"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "5iNub5zJUX88"
},
"source": [
"#### Retorno a los datos\n",
"Perfiles fila de las carreras según las variables activas, para corroborar lo que se ve en los planos factoriales"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"id": "j6KH4xTbUX88",
"outputId": "afe7cf67-0d8f-4fca-a2bf-6d6c0b61095a"
},
"outputs": [
{
"data": {
"image/png": 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AIIIIAAAggggAACCCCAAAIIIIAAAggggAACmRHgFrtkTvW6Ws1KyaxqsbX40rO/\nO+q1xcYygEB7CPg7zJ5qj11lLxHoGIFG1UcdA9TPgSyr8f78rL/AntIcAX/VzBhlahM2R33U\nBORO2gQNpATOpj4U+1ohKvqPKwUBBIJAPpqllxv8vwgedBFoggD1UROQ2UT7CeTys/SQBuqj\n9jtzLdvjZn9RbMsOtMEbHv6LDXeK3j3GnzNMrhzw0DXR7Hd2Fbb78cY8jj05VtbUBIGX75ge\n3fGNx0Y0YVNsAgEEFhdoSH20+CY6b+iD9/+z2P2+0bl3fnP9zju4lB7Rvd97IppyR1dx9S/f\n1NA36+dOuCma+ufPUx+l9PcgrbtFAymBM6P/2cXuXC4anu9KYG1vrcKtolw+F3UNp330lgp9\n7SCQ6+Z3th3OE/vYeQKNqo86T2rxI8qpDs/pzxb17eIujRzK6/WNXuUUc90jGtpAynXxUreR\n57FT182rmE49sxwXAggggAACCCCAAAII1CxAA6lmMhZAAAEEEEAAAQQQQACBThWggdSpZ5bj\nQgABBBBAAAEEEEAAgZoFaCDVTMYCCCCAAAIIIIAAAggg0KkCzWogrSzASaV8vB/MZTTe35ni\n+bbpZ57+Rnv92/c3kfEIIIAAAgiUBKiP+FVAAAEEEBhQoFkNJD/eba1S+msg7aPp/oI7z1fr\n4xgf1TK7KhQEEEAAAQQGEqA+GkiHaQgggAACUbMaSIH6HvW4IbNiGBHrHqz+J0rDudj4anr5\n8q9qlJgHAQQQQCAIUB8FCboIIIAAAosJNLuBdJm2XlD2XWwvomiMhvdQLiqNL8am+2rS15SL\nlVuUC5QDFJfhyrnKMMXrPFMJxbfsnaxcpVyhHKd4PgoCCCCAAALUR/wOIIAAAghUFGh2A2mm\n9uJq5cCyvXHj5gXlzrLxvhXC476svKRcr2ysXKIcrrghNbXUnaPuNMVlrPKg8hXlWeV+5Vjl\nZoVvDBMCBQEEEMi4APVRxn8BOHwEEECgP4FmN5C8H74StIsSv83Ot9f9WSkvvh1vI+VjypeU\nk5R3KTOUDykLlW8pPco1yimKi7vjlc2U/1G83HuU7ZQvKBQEEEAAAQSoj/gdQAABBBBYQqAV\nV1Mu1164QfNR5TeKnyi0m+IrPKsp8XKdBpZSiqWRnndzxVeKfAtdf8WNp1sVNwDXKc20QN3H\nFN/KF78VrzSZDgIIIIBAxgSojzJ2wjlcBCTg14ZHKH59SWm+wCPa5E3N32xtW2xFA2mWdvFf\nij9H5AbS/srjisHKG0gateizRUer64aRP6s0QfEtdJOUSsWfM1pTWVt5psIM/o9BQQABBBBA\ngPqI3wEEsifgN87PU/xgMN+JRGmegO8em6z4brBUl1Y0kAzi2xr+pBiqv9vrNGnRVaa/quvb\n785QblNeUfz0of6Kf9n9eaQrlKMqzOSHRFAQQAABBBCwAPURvwcIZEsgVzrc96rrz79Tmifg\nB6Yd2LzN1b+lVl1NuVK7PF/5grKjEp5ep97Fiq8uuUF0iPL3Uv/S6m6gxBt3vgUvfiy+GrW3\nMk/x55WcN5RzlMMUCgIIIIAAAhagPuL3AAEEEEBgMYF4o2KxCQ0ecGPFV3i+rdynPK1UKr5H\ncWXFt+P5cd9+6MI/lNHKKCWU19Wzi7J7acRJ6vq7kdzw2klZTzlb2Ufxk/AoCCCAAAIIWID6\niN8DBBBAAIHFBFrVQPJO+LYGN3rciOmv/FETPN33iroS8y12NypuAG2quKHkcqays3KNsoLi\nhzscqGyr3KL4M05uJH2y1K8OBQEEEEAAgUUC1Ef8IiCAAAIIvCkQv03tzZEN6JmidYZ7PsPq\nfctc+biry8a5UXSo4i+EXV2ZpITPEH1X/aF8Xz2nKkspr5VGXqquM06Zr0xXKAgggAAC2Rag\nPsr2+efoEUAAgUEFmtVAGnRHBplhgaY/W8U8nq+8uDKkIIAAAgggkIQA9VESiqwDAQQQSLFA\nK2+xSzELu4YAAggggAACCCCAAAJZFKCBlMWzzjEjgAACCCCAAAIIIIBARYHyzwBVnImRAwvk\no9yckfmuYcPy+fD5qIEXqHLqrJ4Fw4rduVz3qK5Ktw5WuRZmQ6D5AsWeYr5nXu9CfWLQj+VP\nQ9lGO7FbGnakRfvwoLbrz3hSOlygUfVRh7NFr6u+zQ3L5bqWor5t1rnueaO3q9gTdeWXWrah\nr3GKvT354sK5C6NiIdRHfmjXBGUNhe9BatYJ79tO+B4k18mpLu3yGaRUIxai4gffKPSMe/Px\nEcnt7QpRT3HYwtd7XkpulawJgaYJpOnzf8foqPdQnmna0adnQ6tpV/w3hAZSes5Jw/akgfVR\nw/Y5JSteubiwWCws7Jmakv3Jwm74wVqrFea+1t9XvSRpkKb6KMnjYl0NEqCBlAzsjcmshrUg\ngECDBHy13N+h9pkGrT/Nqw3v2KV5H9m35ARuTG5VrAkBBBDIpgCfQcrmeeeoEUAAAQQQQAAB\nBBBAoIIAV5AqoNQxagMts1IdyzVikZW10plKQ+/pbcSOs86OE/CtKk903FFxQAikWyBN9VG6\npZbcu3Ea9YrSu+Sklo/p0h64fudWsfpOBfVRfW6ZXYoGUgKnXh+KvVv3fS+bwKqGvIpcdy7S\nB+SHvB5WgMCQBfLRbH0ub/SQ18MKEECgaoE01UdV73RKZqT+TMmJaMRu5PKz9ZCGJOqjkdq9\no5URNezmy5r33BrmZ9YUCNBASuYkDD9zw52j94z1m0+tLdvc/7fCBketlV/voNVbuyNsPdMC\nL90+Pbr9uP8OzzQCB49AawRSUx+15vDr3+qW9/6luOWJ6+fW+sAq9a+kQUs+cNpT0aSr5hbX\n+MZ9PH24RuO5E26Mpv7pM0nVR5to86dutPSYed1RbtB3o2f3Lsw/O2+WG1NDaSDdr+X/qvxA\nGUp5lxa+RNlHeWgoK8rCsjSQEjjL+mtVzOtHVy4lH+nSzuS6+BuawKllFfUK+D8EBQEEmi6Q\nuvqo6QJD26DrzjTWn+HlRS7vO+0otQjkcsnXR7/fdLeRS3cNG3Q37n7t5eiIR28YdL5BZvA7\n3ssPMk81k3s003TFXcogAjSQBgFiMgIIIIAAAggggAACbS5wn/Z/yzY/hqbtfkoueTTteNkQ\nAggggAACCCCAAALtJvAp7fA/lb8oH6+w8+to3M+Vfyn/UX6tbKiE8nb1+Fa/8WGEuisqP1Ku\nVS5Xvq7U8vkqzd6ZJS0NJH9ZGAUBBBBAAIFWC1AftfoMsH0EECgXOEIjvqncoryqnK/8VAll\nG/U8omyn3KlMUPZVfNUoPGXZH5Q/UvHTEF1WVf6rHKh4ve4/XrlLyfzfwVY2kA7QCfid8qTy\nhjJF+beyjdKo4l+e4xq1ctaLAAIIINCWAtRHbXna2GkEMiOwnI50B+XHyueU7yhfUtZVXD6p\nTFPeq3xX+bxyuDJK8bhK5YzSyK3V9TJugO2lbK58Q8l0aVUD6ctS95M03Jr9lfJhxS1hPzrm\nduUTSiPKmlppEh90a8S+sU4EEEAAgeYLUB8135wtIoBAbQK3aXZ/l1Mo56nHzxHYtTTiKHV9\ni91cpUtZV/FrXpdl+jpL/NxNY/6gzIhN8dWnF5Q9Y+My2duKhzS4let7JI9RzixT97DvgXQL\n+WJlvkJBAAEEEECgEQLUR41QZZ0IIJC0wHVlK3Rjya+R1y6N9y1xvurzUWWD0rhHS91cqRvv\njNHACsrE+MhS/zXq+kpSpksrriCdKPHrlfLGkU/EAsWXDe9Q/FjDUNz6PVm5SrlC8W1y5c9X\n9LH43sq/KTcovnTo1jQFAQQQQACBSgLUR5VUGIcAAmkTKG/k+Na5EcpLpR39nbp+bXyp8j5l\nOWU/xaV8WY+bpfQole6qcmPraSXTpdlXkPzBsLcpZw+gfq+mhZPq2cYqdysrKRcqbjUfq7iV\nvLPiE+ziX4q9ld8onn9/5QjFlwl9aZKCAAII1COwhxZ6T40L/knzh3fvalyU2ZskQH3UJGg2\ng0CnCfxq8qPRsPDlVAMc3JQF/oh9ImXHsrWEzxU9qPG+pc4PZDhP+Z4SylalHk8vL37t/H/K\n+5UfxCaOVP+7lcti4zLZ2+wG0vYlZZ/QeBmuAZ8Ul9DS9aXDecopynhlXWWS4uIXH48rX1DO\nVPwBWzeY/AsSTurP1O95zlE2VYoKBQEEEKhJYHiU+8qY4SPfu9bI0b3VLPjYnOldc3p7/Pdr\nKA0kP4HIfxf7KxtpQmI1b38b6fDx1EcdfoI5PAQaIDCpO8r9+6IpT4XXrINuoivKv9gbFQad\nb5AZ3JDxFe9fKxsov1SuVcIFgFvV73k2ViYquyh+/euydF9niZ8naYzvuvqJ4o+++MrRqYrn\nd2Mr06XZDaT+Pih2vM6CG0LxcpoGvq58SPGJ9y106yguvhXvMcXv7LqBtJvixlNoHKk3Wqhc\nrnxZ8QfVJisUBBBAoDaBXBR9YMW1uo9bZ8uq/l4e8tC18x6e/Wpt21hybv/N8t+4fy05adEY\n/32jDE2A+mhofiyNQBYFpvVExQ/0FKt6vyxJH7/p/xHFr5X9hr9f335KCeU76nFD55HSiKfU\nPUz5obJDaVx55+8acbjyU8Wvt31QDyh+be1upktVFX6CQreX1rW1um75hvIX9fhqTygXl3qG\nqesXCmsrz5TGxTtuNLmsr0x0T1m5RsNuIHl5GkhlOAwigECqBe7R3rnSozRGgPqoMa6sFQEE\nkhVYJba6NdQ/S3ktNs69dyrvUfxxFJepfZ3o6lLXnfCaOd66+73GO2spXmf5ejUqm6XZDaRn\nxTxF8Un8UYzc75Q6oYQGkt8lnaNcoRwVJsa64ZrldI3bIDY+9Pp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isFz3yJ6oBa936kUrFnpzUaFnQVQsuDHhsp4yQVlDqfXKiR+KcKLi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J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",
"text/plain": [
"Plot with title “edad”"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"par(mfrow=c(2,2))\n",
"for (varac in 8:11){\n",
" K<-unclass(table(admi$carr,admi[,varac]))\n",
" plotct(K,\"row\",col=2:5,main=colnames(admi)[varac])\n",
"}"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "dBxPugA5UX88"
},
"source": [
"- Química tiene, en comparación al promedio, mayor proporción de admitidos de estrato bajo y origen fuera de Bogotá,\n",
"- Matemáticas tiene mayor proporción de admitidos de 19 o más años, \n",
"- Geología tiene mayor proporción de admitidos de 17 años y de estrato alto, \n",
"- Farmacia tiene mayor proporción de admitidos de 18 años y género femenino. \n"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "NVY7hfZyUX88"
},
"source": [
"Para más detalles del ACM y un ejemplo de aplicación ver el capítulo 6 del libro [EDM.](https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwi6qZDBjtDzAhVeRTABHYZPBWEQFnoECAYQAQ&url=http%3A%2F%2Fciencias.bogota.unal.edu.co%2Ffileadmin%2FFacultad_de_Ciencias%2FPublicaciones%2FImagenes%2FPortadas_Libros%2FEstadistica%2FEstadistica_descriptiva_multivariada%2FlibroEstadisiticaDescriptivaMultivariadaDigital.pdf&usg=AOvVaw2Q7b-e89FbWXFda5h4sCuf)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Ejemplo de aplicación: ACM de consumo cultural entre niños de 8 a 11 años en Colombia"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Se presenta un ejemplo de análisis parcial de la Encuesta de Consumo Cultural 2014 (Dane). La encuesta aplica un formulario a una subpoblación de niños de 5 a 11 años, sobre consumo cultural. Se adicionan algunas variables sociodemográficas de los módulos de hogares y viviendas. Para este análisis, se seleccionan los niños que tienen edades entre 8 y 11 años y que saben leer. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Objetivos del análisis\n",
"\n",
"Describir el consumo cultural de niños entre 8 y 11 años, que saben leer y explorar su relación con algunas variables sociodemográficas.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Datos\n",
"\n",
"Para este ejemplo se toman las siguientes preguntas del tema de consumo cultural:\n",
"\n",
"- Teat: ¿El niño o la niña asistió a teatro, danza u ópera en los últimos doce meses?\t¿Con qué frecuencia?\n",
"- Libr: ¿En los últimos doce meses el niño o la niña leyó libros y con qué frecuencia?\n",
"- Cine: ¿En los últimos doce meses el niño o la niña fue a cine y con qué frecuencia?\n",
"- Vide: ¿El niño o la niña vio videos en el último mes y con qué frecuencia?\n",
"- Radi: ¿En la última semana el niño o la niña escuchó radio y con qué frecuencia?\n",
"- Musi: ¿El niño o la niña escuchó música grabada en la última semana y con qué frecuencia?\n",
"\n",
"La tabla activa construida para este análisis tiene 1971 niños de todo el país y seis variables cualitativas sobre consumo cultural.\n",
"\n",
"El formulario de la encuesta tiene dos preguntas para cada actividad: la primera, si se ha realizado, y la segunda, su frecuencia. Las respuestas a las dos preguntas en cada actividad, se recodificaron en una sola y se incluyó la categoría no como otro ítem de frecuencia. Adicionalmente se unieron algunas categorías de muy baja frecuencia. \n",
"\n",
"Las distribuciones de frecuencias de las variables se muestran en forma de tortas en la figura donde se pueden ver sus categorías. Se tienen entonces $s=6$ variables activas con un total de $p=31$ categorías.\n"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
"rm(list=ls())\n",
"# Lectura de los datos, están en formato R\n",
"load(\"../Datos/ninios8a11.rda\")\n",
"# variables activas\n",
"Y <- subset(ninios8a11,select=c(Teat,Libr,Cine,Vide,Radi,Musi))\n",
"# variables suplementarias\n",
"Ys<-ninios8a11[,c(2,29,30,32,35)]"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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CNRKgg1QjeBaLAAIIIIAAAggggAAC6ROgg5S+fcIaIYAAAggggAACCCCAQI0E6CDV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\nrFCitZZG9lU2Vf6gvKxQnQgkfQfpBK3PDsE6ubHZqpP1420E4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o0wXsojzu2jfSneXhbaB7QvcR595c+L9qV8O3+z0LEd/uypbM6rfpv2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\nAAIIIIAAAggggEADCPx/i/ooYf9/FToAAAAASUVORK5CYII=",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"par(las=1,mfrow=c(2,3),mai=c(0.55,0.5,0.1,0.1))\n",
"for(i in 1:6){\n",
" cat<-attributes(Y[,i])$levels;\n",
" per<-tabulate(Y[,i])/nrow(Y)*100;\n",
" pl<-plot(Y[,i],horiz=TRUE,col=gray(seq(1.0,0.9,\n",
" length=length(cat))),ylim=c(0,8),\n",
" xlim=c(0,1400),xlab=colnames(Y)[i]);\n",
" text(800,pl,round(per,1),cex=0.8,pos=4); \n",
" } \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Las variables ilustrativas se muestran en la figura junto con las distribuciones de frecuencias. Las variables estrato y parentesco, se recodificaron a menos categorías, dada la presencia de frecuencias muy bajas en algunas de ellas."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Corrección de edad:** la variable *Edad* es cualitativa (categórica), y tiene tres categorías sin frecuencias, vamos a eliminarlas así: "
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"\n",
" a5 a6 a7 a8 a9 a10 a11 \n",
" 0 0 0 467 474 510 520 "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"\n",
" a8 a9 a10 a11 \n",
"467 474 510 520 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"table(Ys$Edad) #para ver las frecuencias como venían\n",
"Ys$Edad=factor(as.numeric(Ys$Edad),labels=paste(\"a\",8:11,sep=\"\"))\n",
"table(Ys$Edad) #ver las frecuencias como quedaron "
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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hMgQIAAAQIECBAgMHECGkgTZ2lOBAgQIECAAAECBAj0uIAGUo/vQKtPgAABAgQI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\ngAIKKKCAAgoooIACCiigwDgL/C+Z399/ZJOsDgAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"\n",
"par(las=1,mfrow=c(2,3),mai=c(0.55,0.5,0.1,0.1))\n",
"for(i in 1:5){\n",
" cat<-attributes(Ys[,i])$levels;\n",
" per<-tabulate(Ys[,i])/nrow(Y)*100;\n",
" pl<-plot(Ys[,i],horiz=TRUE,col=gray(seq(1.0,0.9,\n",
" length=length(cat))),ylim=c(0,8),\n",
" xlim=c(0,1400),xlab=colnames(Ys)[i]);\n",
" text(800,pl,round(per,1),cex=0.8,pos=4); \n",
"} \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Resultados del análisis\n",
"Para realizar el ACM se usa la función *dudi.acm{ade4}*; las ayudas para la interpretación se obtienen con *inertia.dudi{ade4}*; las coordenadas y ayudas para la interpretación de las variables cualitativas ilustrativas, con \n",
"*supqual{FactoClass}*; los planos factoriales, con *plot.dudi{FactoClass}* para las variables activas \n",
"y *plotfp{FactoClass}* para los planos factoriales cuando se desean solo las variables cualitativas ilustrativas. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Número de ejes a interpretar\n",
"La primera decisión a tomar es el número de ejes a interpretar. No hay recetas pero sí criterios que ayudan a tomar esta decisión. La guía principal es la forma del histograma de valores propios. \n",
"\n",
"- Los ejes que sobresalen claramente, antes de ver una forma de $S$ regular del histograma serían los ejes a analizar. \n",
"\n",
"- El criterio de Benzécri, que utiliza un histograma de una transformación de los valores propios, considerando los que son superiores a $1/s$, también ayuda. \n",
"\n",
"- Finalmente, en concordancia con los objetivos, se debe interpretar un eje adicional si provee información relevante que no se ha obtenido con los ejes anteriores.\n",
"\n",
"Para el ejemplo se muestran en la figura los histogramas de valores propios y del criterio de Benzécri, los valores propios y porcentajes de inercia. Los gráficos sugieren analizar tres ejes. \n",
"\n",
"El criterio de Benzécri se construye considerando los 11 valores propios, que tienen un valor superior a $1/6= 0.1667$. Los tres primeros ejes retienen el 17.8\\% de la inercia, pero en el ACM este es un índice pesimista. \n",
"\n",
"En el criterio de Benzècri se retiene un 81.8% de la variabilidad ajustada, pues el criterio considera que 25 - 11 = 14 ejes son \"parásitos\", es decir, no suministran información. El bajo porcentaje de inercia retenida en los ejes, hace que el analista tenga que ser menos exigente en las calidades de las representaciones."
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 8 × 12</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>eje</th><th scope=col>valp</th><th scope=col>porc</th><th scope=col>pacu</th><th scope=col>eje</th><th scope=col>valp</th><th scope=col>porc</th><th scope=col>pacu</th><th scope=col>eje</th><th scope=col>valp</th><th scope=col>porc</th><th scope=col>pacu</th></tr>\n",
"\t<tr><th></th><th scope=col><int></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><int></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><int></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>1</th><td>1</td><td>0.3007</td><td>7.2158</td><td> 7.2158</td><td> 9</td><td>0.1715</td><td>4.1160</td><td>44.0120</td><td>17</td><td>0.1513</td><td>3.6310</td><td>74.8790</td></tr>\n",
"\t<tr><th scope=row>2</th><td>2</td><td>0.2323</td><td>5.5752</td><td>12.7910</td><td>10</td><td>0.1689</td><td>4.0527</td><td>48.0648</td><td>18</td><td>0.1442</td><td>3.4608</td><td>78.3399</td></tr>\n",
"\t<tr><th scope=row>3</th><td>3</td><td>0.2089</td><td>5.0141</td><td>17.8051</td><td>11</td><td>0.1680</td><td>4.0324</td><td>52.0971</td><td>19</td><td>0.1432</td><td>3.4360</td><td>81.7758</td></tr>\n",
"\t<tr><th scope=row>4</th><td>4</td><td>0.1952</td><td>4.6838</td><td>22.4889</td><td>12</td><td>0.1648</td><td>3.9556</td><td>56.0527</td><td>20</td><td>0.1402</td><td>3.3651</td><td>85.1409</td></tr>\n",
"\t<tr><th scope=row>5</th><td>5</td><td>0.1879</td><td>4.5105</td><td>26.9994</td><td>13</td><td>0.1609</td><td>3.8612</td><td>59.9139</td><td>21</td><td>0.1350</td><td>3.2407</td><td>88.3816</td></tr>\n",
"\t<tr><th scope=row>6</th><td>6</td><td>0.1809</td><td>4.3422</td><td>31.3416</td><td>14</td><td>0.1589</td><td>3.8127</td><td>63.7266</td><td>22</td><td>0.1315</td><td>3.1566</td><td>91.5382</td></tr>\n",
"\t<tr><th scope=row>7</th><td>7</td><td>0.1804</td><td>4.3292</td><td>35.6708</td><td>15</td><td>0.1584</td><td>3.8006</td><td>67.5273</td><td>23</td><td>0.1292</td><td>3.1017</td><td>94.6399</td></tr>\n",
"\t<tr><th scope=row>8</th><td>8</td><td>0.1761</td><td>4.2253</td><td>39.8961</td><td>16</td><td>0.1550</td><td>3.7207</td><td>71.2480</td><td>24</td><td>0.1213</td><td>2.9106</td><td>97.5504</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 8 × 12\n",
"\\begin{tabular}{r|llllllllllll}\n",
" & eje & valp & porc & pacu & eje & valp & porc & pacu & eje & valp & porc & pacu\\\\\n",
" & <int> & <dbl> & <dbl> & <dbl> & <int> & <dbl> & <dbl> & <dbl> & <int> & <dbl> & <dbl> & <dbl>\\\\\n",
"\\hline\n",
"\t1 & 1 & 0.3007 & 7.2158 & 7.2158 & 9 & 0.1715 & 4.1160 & 44.0120 & 17 & 0.1513 & 3.6310 & 74.8790\\\\\n",
"\t2 & 2 & 0.2323 & 5.5752 & 12.7910 & 10 & 0.1689 & 4.0527 & 48.0648 & 18 & 0.1442 & 3.4608 & 78.3399\\\\\n",
"\t3 & 3 & 0.2089 & 5.0141 & 17.8051 & 11 & 0.1680 & 4.0324 & 52.0971 & 19 & 0.1432 & 3.4360 & 81.7758\\\\\n",
"\t4 & 4 & 0.1952 & 4.6838 & 22.4889 & 12 & 0.1648 & 3.9556 & 56.0527 & 20 & 0.1402 & 3.3651 & 85.1409\\\\\n",
"\t5 & 5 & 0.1879 & 4.5105 & 26.9994 & 13 & 0.1609 & 3.8612 & 59.9139 & 21 & 0.1350 & 3.2407 & 88.3816\\\\\n",
"\t6 & 6 & 0.1809 & 4.3422 & 31.3416 & 14 & 0.1589 & 3.8127 & 63.7266 & 22 & 0.1315 & 3.1566 & 91.5382\\\\\n",
"\t7 & 7 & 0.1804 & 4.3292 & 35.6708 & 15 & 0.1584 & 3.8006 & 67.5273 & 23 & 0.1292 & 3.1017 & 94.6399\\\\\n",
"\t8 & 8 & 0.1761 & 4.2253 & 39.8961 & 16 & 0.1550 & 3.7207 & 71.2480 & 24 & 0.1213 & 2.9106 & 97.5504\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 8 × 12\n",
"\n",
"| <!--/--> | eje <int> | valp <dbl> | porc <dbl> | pacu <dbl> | eje <int> | valp <dbl> | porc <dbl> | pacu <dbl> | eje <int> | valp <dbl> | porc <dbl> | pacu <dbl> |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| 1 | 1 | 0.3007 | 7.2158 | 7.2158 | 9 | 0.1715 | 4.1160 | 44.0120 | 17 | 0.1513 | 3.6310 | 74.8790 |\n",
"| 2 | 2 | 0.2323 | 5.5752 | 12.7910 | 10 | 0.1689 | 4.0527 | 48.0648 | 18 | 0.1442 | 3.4608 | 78.3399 |\n",
"| 3 | 3 | 0.2089 | 5.0141 | 17.8051 | 11 | 0.1680 | 4.0324 | 52.0971 | 19 | 0.1432 | 3.4360 | 81.7758 |\n",
"| 4 | 4 | 0.1952 | 4.6838 | 22.4889 | 12 | 0.1648 | 3.9556 | 56.0527 | 20 | 0.1402 | 3.3651 | 85.1409 |\n",
"| 5 | 5 | 0.1879 | 4.5105 | 26.9994 | 13 | 0.1609 | 3.8612 | 59.9139 | 21 | 0.1350 | 3.2407 | 88.3816 |\n",
"| 6 | 6 | 0.1809 | 4.3422 | 31.3416 | 14 | 0.1589 | 3.8127 | 63.7266 | 22 | 0.1315 | 3.1566 | 91.5382 |\n",
"| 7 | 7 | 0.1804 | 4.3292 | 35.6708 | 15 | 0.1584 | 3.8006 | 67.5273 | 23 | 0.1292 | 3.1017 | 94.6399 |\n",
"| 8 | 8 | 0.1761 | 4.2253 | 39.8961 | 16 | 0.1550 | 3.7207 | 71.2480 | 24 | 0.1213 | 2.9106 | 97.5504 |\n",
"\n"
],
"text/plain": [
" eje valp porc pacu eje valp porc pacu eje valp porc pacu \n",
"1 1 0.3007 7.2158 7.2158 9 0.1715 4.1160 44.0120 17 0.1513 3.6310 74.8790\n",
"2 2 0.2323 5.5752 12.7910 10 0.1689 4.0527 48.0648 18 0.1442 3.4608 78.3399\n",
"3 3 0.2089 5.0141 17.8051 11 0.1680 4.0324 52.0971 19 0.1432 3.4360 81.7758\n",
"4 4 0.1952 4.6838 22.4889 12 0.1648 3.9556 56.0527 20 0.1402 3.3651 85.1409\n",
"5 5 0.1879 4.5105 26.9994 13 0.1609 3.8612 59.9139 21 0.1350 3.2407 88.3816\n",
"6 6 0.1809 4.3422 31.3416 14 0.1589 3.8127 63.7266 22 0.1315 3.1566 91.5382\n",
"7 7 0.1804 4.3292 35.6708 15 0.1584 3.8006 67.5273 23 0.1292 3.1017 94.6399\n",
"8 8 0.1761 4.2253 39.8961 16 0.1550 3.7207 71.2480 24 0.1213 2.9106 97.5504"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"1/s: 0.1667"
]
}
],
"source": [
"acm<-dudi.acm(Y,scannf = FALSE,nf=3)\n",
"eigtab<-data.frame(valp=acm$eig,porc=acm$eig/sum(acm$eig)*100,\n",
" pacu=cumsum(acm$eig)/sum(acm$eig)*100)\n",
"cbind(eje=1:8,round(eigtab[1:8,],4),eje=9:16,round(eigtab[9:16,],4),\n",
" eje=17:24,round(eigtab[17:24,],4))\n",
"# ,digits=c(0,rep(c(0,3,1,1),3)))\n",
"# criterio de Benzecri\n",
"s<-6; cat(\"\\n1/s:\",round(1/s,4)) \n",
"# --> se calcula tau para los primeros 11 ejes\n",
"eig11<-acm$eig[1:11]\n",
"tau<-(s/(s-1))^2*(eig11-(1/s))^2\n",
"ptau<-tau/sum(tau)*100"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Histograma de valores propios"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Altura linea verde = 1/s"
]
},
{
"data": {
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wVqLJCSMz8HKQucPIL00IirI/KKc6Na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\nRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"barplot(acm$eig,las=2)\n",
"abline(h=1/s,col=\"darkgreen\")\n",
"cat(\"\\nAltura linea verde = 1/s\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Criterio de Benzècri"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Altura linea azul = promedio de los taus"
]
},
{
"data": {
"image/png": 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hIQkBqCdhkCBAgQIECAAAECBNovICC1\nv0dmSIAAAQIECBAgQIBAQwICUkPQLkOAAAECBAgQIECAQPsFBKT298gMCRAgQIAAAQIECBBo\nSEBAagjaZQgQIECAAAECBAgQaL+AgNT+HpkhAQIECBAgQIAAAQINCQhIDUG7DAECBAgQIECA\nAAEC7RcQkNrfIzMkQIAAAQIECBAgQKAhAQGpIWiXIUCAAAECBAgQIECg/QICUvt7ZIYECBAg\nQIAAAQIECDQkICA1BO0yBAgQIECAAAECBAi0X0BAan+PzJAAAQIECBAgQIAAgYYEBKSGoF2G\nAAECBAgQIECAAIH2CwhI7e+RGRIgQIAAAQIECBAg0JCAgNQQtMsQIECAAAECBAgQINB+AQGp\n/T0yQwIECBAgQIAAAQIEGhIQkBqCdhkCBAgQIECAAAECBNovICC1v0dmSIAAAQIECBAgQIBA\nQwICUkPQLkOAAAECBAgQIECAQPsFBKT298gMCRAgQIAAAQIECBBoSEBAagjaZQgQIECAAAEC\nBAgQaL+AgNT+HpkhAQIECBAgQIAAAQINCQhIDUG7DAECBAgQIECAAAEC7RcQkNrfIzMkQIAA\nAQIECBAgQKAhAQGpIWiXIUCAAAECBAgQIECg/QICUvt7ZIYECBAgQIAAAQIECDQkICA1BO0y\nBAgQIECAAAECBAi0X0BAan+PzJAAAQIECBAgQIAAgYYEBKSGoF2GAAECBAgQIECAAIH2CwhI\n7e+RGRIgQIAAAQIECBAg0JCAgNQQtMsQIECAAAECBAgQINB+AQGp/T0yQwIECBAgQIAAAQIE\nGhIQkBqCdhkCBAgQIECAAAECBNovMNf+KRbP8NXxDgdHrY/6VtRDUYuNbWLjIVF7RN0SdVeU\nQYAAAQIECBAgQIBAjwRqDkg7RR8/E/Weef1cF88/HHXevG35dO+oL0Ttmy8G49Z4PCLq3uEG\njwQIECBAgAABAgQI1C1Q81fsvhKty3CUYeiNUb8R9d2oc6OOihqO2XhyWdSeUcdEZVg6Meq1\nUTdE7RBlECBAgAABAgQIECDQA4FaP0H6p9G7n4+6OOp3B338P/F4U9R3ok6K+tOoHPn8sMHj\nFbkhxt2bH2Yuicejo/J9DAIECBAgQIAAAQIEKheo9ROk06Nvj0e9f0H/8mtzb4/6nXnbj43n\nz0VdOW9bPs3X+ZW8E/KFQYAAAQIECBAgQIBA/QK1foKUN2X4q6gMOPkVuv2j8iYMGZC+GjUc\nK+PJgVF3RGWgmj+ejBe3Rx0Qlce9EGUQIECAAAECBAgQIFCxQI0BKW/OsGPU30flb5Dya3K7\nReVYG5W/L/qzfBFjl6hVUY/mi0VGHp/haPeo+xfZv9Sm18fOfO9JRx5786QHO44AAQIECBAg\nQIAAgZdeoMaAlDdbyJG/K8qvx/1R1A1Rr4s6M+qqqLw73ZeiMkzleGTzw4/8NQNSjuXeqOFn\n4pzbovLTq0nHpjgww9iGSU9wHAECBAgQIECAAAECL61AjQFpGHreGFS/HvVf5pHln4OUd7f7\neNR+UfkVvByjfouVX8vLsdzQkjd52DkqA88k4+fioP8Rlddb7rUmeX/HECBAgAABAgQIECAw\ngUCNAemBwbofjsf54Sg3fy3qwah9ozLA5PP85GbXqMXGcPsTi+0csy1/wzTpWM6xk76n4wgQ\nIECAAAECBAgQWKbAqE9Olvk2rTo8fyu0MeqhRWaV2zMk5cjfFa2PyuOGQSiebjFy+zNRC2/g\nsMVBXhAgQIAAAQIECBAgUIdAjQEpQ09+xS1vkvCyRdq0R2x7LCqPyZG/Fcq73A1v5JDbcmSA\nyq/h5Y0TfO0tEAwCBAgQIECAAAECtQvUGJCyZx+Lyq8PnpEv5o38XdJhUV+Pyq/W5bgoKo89\nLl/MG8fH89x+4bxtnhIgQIAAAQIECBAgULFAjb9BynZ9Ouq3os6Jyk+C/iJqr6g/iMo71p0W\nNRzXxJP8FOm8qB2jro9aHZV3vLs6Ku96ZxAgQIAAAQIECBAg0AOBWgPSc9G7Q6I+GXVC1MlR\n+dW7m6JOjfpu1HDk75IOj7o86qyos6NyXBuV5xkECBAgQIAAAQIECPREoNaAlO17KupXo34j\nKu9ad09Ublts5KdK74zKT5D2ibovKu9wZxAgQIAAAQIECBAg0COBmgPSsI3Px5Nbhi/GPGaA\nypsyGAQIECBAgAABAgQI9FCg1ps09LCVlkyAAAECBAgQIECAQKmAgFQq6HwCBAgQIECAAAEC\nBKoREJCqaaWFECBAgAABAgQIECBQKiAglQo6nwABAgQIECBAgACBagQEpGpaaSEECBAgQIAA\nAQIECJQKCEilgs4nQIAAAQIECBAgQKAaAQGpmlZaCAECBAgQIECAAAECpQICUqmg8wkQIECA\nAAECBAgQqEZAQKqmlRZCgAABAgQIECBAgECpgIBUKuh8AgQIECBAgAABAgSqERCQqmmlhRAg\nQIAAAQIECBAgUCogIJUKOp8AAQIECBAgQIAAgWoEBKRqWmkhBAgQIECAAAECBAiUCghIpYLO\nJ0CAAAECBAgQIECgGgEBqZpWWggBAgQIECBAgAABAqUCAlKpoPMJECBAgAABAgQIEKhGQECq\nppUWQoAAAQIECBAgQIBAqYCAVCrofAIECBAgQIAAAQIEqhEQkKpppYUQIECAAAECBAgQIFAq\nICCVCjqfAAECBAgQIECAAIFqBASkalppIQQIECBAgAABAgQIlAoISKWCzidAgAABAgQIECBA\noBoBAamaVloIAQIECBAgQIAAAQKlAgJSqaDzCRAgQIAAAQIECBCoRkBAqqaVFkKAAAECBAgQ\nIECAQKmAgFQq6HwCBAgQIECAAAECBKoREJCqaaWFECBAgAABAgQIECBQKiAglQo6nwABAgQI\nECBAgACBagQEpGpaaSEECBAgQIAAAQIECJQKCEilgs4nQIAAAQIECBAgQKAaAQGpmlZaCAEC\nBAgQIECAAAECpQICUqmg8wkQIECAAAECBAgQqEZAQKqmlRZCgAABAgQIECBAgECpgIBUKuh8\nAgQIECBAgAABAgSqERCQqmmlhRAgQIAAAQIECBAgUCogIJUKOp8AAQIECBAgQIAAgWoEBKRq\nWmkhBAgQIECAAAECBAiUCghIpYLOJ0CAAAECBAgQIECgGgEBqZpWWggBAgQIECBAgAABAqUC\nAlKpoPMJECBAgAABAgQIEKhGQECqppUWQoAAAQIECBAgQIBAqYCAVCrofAIECBAgQIAAAQIE\nqhEQkKpppYUQIECAAAECBAgQIFAqICCVCjqfAAECBAgQIECAAIFqBASkalppIQQIECBAgAAB\nAgQIlAoISKWCzidAgAABAgQIECBAoBoBAamaVloIAQIECBAgQIAAAQKlAgJSqaDzCRAgQIAA\nAQIECBCoRkBAqqaVFkKAAAECBAgQIECAQKmAgFQq6HwCBAgQIECAAAECBKoREJCqaaWFECBA\ngAABAgQIECBQKiAglQo6nwABAgQIECBAgACBagQEpGpaaSEECBAgQIAAAQIECJQKCEilgs4n\nQIAAAQIECBAgQKAaAQGpmlZaCAECBAgQIECAAAECpQICUqmg8wkQIECAAAECBAgQqEZAQKqm\nlRZCgAABAgQIECBAgECpgIBUKuh8AgQIECBAgAABAgSqERCQqmmlhRAgQIAAAQIECBAgUCog\nIJUKOp8AAQIECBAgQIAAgWoEBKRqWmkhBAgQIECAAAECBAiUCghIpYLOJ0CAAAECBAgQIECg\nGgEBqZpWWggBAgQIECBAgAABAqUCAlKpoPMJECBAgAABAgQIEKhGQECqppUWQoAAAQIECBAg\nQIBAqYCAVCrofAIECBAgQIAAAQIEqhEQkKpppYUQIECAAAECBAgQIFAqICCVCjqfAAECBAgQ\nIECAAIFqBASkalppIQQIECBAgAABAgQIlAoISKWCzidAgAABAgQIECBAoBoBAamaVloIAQIE\nCBAgQIAAAQKlAnOlb9Di83eKue0yYn4/iO2PLNi3Tbw+JGqPqFui7ooyCBAgQIAAAQIECBDo\nkUDNAekj0cd/PaKX/zW2/6t5+/aO51+I2nfetlvj+RFR987b5ikBAgQIECBAgAABAhUL1ByQ\nDoy+PR116SL9u3nettl4flnUnlHHRK2JemvUJ6JuiNo/Kj9xMggQIECAAAECBAgQqFyg1oCU\nv616Y9RfR31gTA9Piv2HReXjFYNj7x48XhKPR0ddPHjtgQABAgQIECBAgACBigVqvUlDfmVu\nh6j/PUHvjo1jnou6csGx+Xpd1AkLtntJgAABAgQIECBAgEClArV+gpRfr8uRX6U7NOrgqCej\n8utzd0QNx8p4ksfmtseHGwePefztUQdE5XEvRBkECBAgQIAAAQIECFQsUHtA+nD0Lj9NGo6N\n8SR/W3RG1PqovMvdqqhHoxYba2NjhqPdo+5f7IAx2/L3TQYBAgQIECBAgAABAh0RqPUrdgcN\n/B+Mx1+K2mvweFs85m+SPhiVI28FnmPhLb83b52ZyYCUI7+ut5zxujg4P3HKQDZJfWM5b+5Y\nAgQIECBAgAABAgSmI1DrJ0h/GFz/LepPovJ3RDm+F/WtqPza3NlRH4sa7hsVFPPPRsqxYfPD\nxH/9bhyZN37IT6cmGW+Ig/7TJAc6hgABAgQIECBAgACB6QnUGpD+V5BlLRz5idKXo94blbfv\nzsC0KWrXqMXGcPsTi+1cYlu+Z/7eadLh902TSjmOAAECBAgQIECAwBQFRn1yMsVLbvW3fngw\ng/x6Xf4O6aGoYRAa7HrxIbc/E7XwBg4vHuAJAQIECBAgQIAAAQL1CNQYkHaM9uTd6/J3PYut\nb99B+4Z3s8vfJeWnSbsNtg8f8sYM+0Xley33K3bD9/BIgAABAgQIECBAgECHBBYLEB2a/qJT\nfSq25m9/3hKVX6WbP34hXqyO+mpU/iYpx0VR+VXD4/LFvHF8PM/tF87b5ikBAgQIECBAgAAB\nAhUL1PobpPdHz66NyhsfHBL1l1FvivpQ1GNReSe74bgmnuSnSOdF5adP10etjjoz6uqoq6IM\nAgQIECBAgAABAgR6IFDjJ0jZtuui3hWVt+n+t1F5Y4Zzo/426ueibokajrwN9+FRGajOispj\n8/ErUSdHGQQIECBAgAABAgQI9ESg1k+Qsn1fHNQe8ZiVt/fOGy4sNvLPQXpnVH6CtE/UfVF5\nxzuDAAECBAgQIECAAIEeCdQckIZtfCCeZE0y8vdLeVMGgwABAgQIECBAgACBHgrU+hW7HrbS\nkgkQIECAAAECBAgQKBUQkEoFnU+AAAECBAgQIECAQDUCAlI1rbQQAgQIECBAgAABAgRKBQSk\nUkHnEyBAgAABAgQIECBQjYCAVE0rLYQAAQIECBAgQIAAgVIBAalU0PkECBAgQIAAAQIECFQj\nICBV00oLIUCAAAECBAgQIECgVEBAKhV0PgECBAgQIECAAAEC1QgISNW00kIIECBAgAABAgQI\nECgVEJBKBZ1PgAABAgQIECBAgEA1AgJSNa20EAIECBAgQIAAAQIESgUEpFJB5xMgQIAAAQIE\nCBAgUI2AgFRNKy2EAAECBAgQIECAAIFSAQGpVND5BAgQIECAAAECBAhUIyAgVdNKCyFAgAAB\nAgQIECBAoFRAQCoVdD4BAgQIECBAgAABAtUICEjVtNJCCBAgQIAAAQIECBAoFRCQSgWdT4AA\nAQIECBAgQIBANQICUjWttBACBAgQIECAAAECBEoFBKRSQecTIECAAAECBAgQIFCNgIBUTSst\nhAABAgQIECBAgACBUgEBqVTQ+QQIECBAgAABAgQIVCMgIFXTSgshQIAAAQIECBAgQKBUQEAq\nFXQ+AQIECBAgQIAAAQLVCAhI1bTSQggQIECAAAECBAgQKBUQkEoFnU+AAAECBAgQIECAQDUC\nAlI1rbQQAgQIECBAgAABAgRKBQSkUkHnEyBAgAABAgQIECBQjYCAVE0rLYQAAQIECBAgQIAA\ngVIBAalU0PkECBAgQIAAAQIECFQjICBV00oLIUCAAAECBAgQIECgVEBAKhV0PgECBAgQIECA\nAAEC1QgISNW00kIIECBAgAABAgQIECgVEJBKBZ1PgAABAgQIECBAgEA1AgJSNa20EAIECBAg\nQIAAAQIESgUEpFJB5xMgQIAAAQIECBAgUI2AgFRNKy2EAAECBAgQIECAAIFSAQGpVND5BAgQ\nIECAAAECBAhUIyAgVdNKCyFAgAABAgQIECBAoFRAQCoVdD4BAgQIECBAgAABAtUICEjVtNJC\nCBAgQIAAAQIECBAoFRCQSgWdT4AAAQIECBAgQIBANQICUjWttBACBAgQIECAAAECBEoFBKRS\nQecTIECAAAECBAgQIFCNgIBUTSsthAABAgQIECBAgACBUgEBqVTQ+QQIECBAgAABAgQIVCMg\nIFXTSgshQIAAAQIECBAgQKBUQEAqFXQ+AQIECBAgQIAAAQLVCAhI1bTSQggQIECAAAECBAgQ\nKBUQkEoFnU+AAAECBAgQIECAQDUCAlI1rbQQAgQIECBAgAABAgRKBQSkUkHnEyBAgAABAgQI\nECBQjYCAVE0rLYQAAQIECBAgQIAAgVIBAalU0PkECBAgQIAAAQIECFQjICBV00oLIUCAAAEC\nBAgQIECgVEBAKhV0PgECBAgQIECAAAEC1QgISNW00kIIECBAgAABAgQIECgVEJBKBZ1PgAAB\nAgQIECBAgEA1AgJSNa20EAIECBAgQIAAAQIESgUEpFJB5xMgQIAAAQIECBAgUI2AgFRNKy2E\nAAECBAgQIECAAIFSAQGpVND5BAgQIECAAAECBAhUIyAgVdNKCyFAgAABAgQIECBAoFRAQCoV\ndD4BAgQIECBAgAABAtUICEjVtNJCCBAgQIAAAQIECBAoFRCQSgWdT4AAAQIECBAgQIBANQIC\nUjWttBACBAgQIECAAAECBEoFBKRSQecTIECAAAECBAgQIFCNgIBUTSsthAABAgQIECBAgACB\nUgEBqVTQ+QQIECBAgAABAgQIVCMgIFXTSgshQIAAAQIECBAgQKBUoE8B6ScD6z1Ru45A2ya2\nHxp1ZNTeI46xmQABAgQIECBAgACBigX6EpAy/FwV9edRr1+knxmIvh319ag87s6o70TtFWUQ\nIECAAAECBAgQINATgb4EpLOin28Z0dPZ2H5Z1J5Rx0RlWDox6rVRN0TtEGUQIECAAAECBAgQ\nINADgbkerPHNscYPRT0ctfsi6z0pth0WlY9XDPbfPXi8JB6Pjrp48NoDAQIECBAgQIAAAQIV\nC9T+CVJ++vPZqDVRfzzo46bB4/Dh2HjyXNSVww2Dx3y9LuqEBdu9JECAAAECBAgQIECgUoHa\nA9LHom+vivq1qA2L9HBlbDswKn9z9PiC/U/G69ujDojK4wwCBAgQIECAAAECBCoXqDkgvTt6\n976o90fdM6KPu8T2VVGPjti/NrZnOFrsq3kjTrGZAAECBAgQIECAAIGuCtT6G6RXR0Mujfp8\n1KeWaM5Og32PjDgmA1KO5d6oYa845y+iJv3kafu8iEGAAAECBAgQIECAwNYVqDUgZSjaGJWf\nIC018jdGOUZ9kpa3B8+x2NfzNu9Z/K8Pxeb/GJWfTk0y8o55p09yoGMIECBAgAABAgQIEJie\nQI0B6ZTgemfUUVE/iHpZVI7hpznbxfPc9mzUg1F504ZRf3jscPsTccxyRt70IT/BmnTkLcgF\npEm1HEeAAAECBAgQIEBgSgI1BqQjB1Z/OsLsa4Pt+8bjHVH5ac8wCA12vfiQ25+JWngDhxcP\n8IQAAQIECBAgQIAAgXoEagxIV0d7vr1Ii34htr0p6nNR+cnRY1E5bov6xajdoub/FilvzLBf\n1DejlvsVuzjFIECAAAECBAgQIECgawI1BqSLRjThI7E9A9J/iFoz75g8fnXUcVEfjRqO4+NJ\n+lw43OCRAAECBAgQIECAAIG6BWoMSMvt2DVxQn6KdF7UjlHXR62OOjMqP426KsogQIAAAQIE\nCBAgQKAHAgLS5rvdHR69vjzqrKizB32/Nh5PHjz3QIAAAQIECBAgQIBADwT6FJA+GP3MWmzk\nb4/yznf5CdI+UfdF5e+UDAIECBAgQIAAAQIEeiTQp4A0SVufioNunuRAxxAgQIAAAQIECBAg\nUJ/AqD8gtb6VWhEBAgQIECBAgAABAgTGCAhIY4DsJkCAAAECBAgQIECgPwICUn96baUECBAg\nQIAAAQIECIwREJDGANlNgAABAgQIECBAgEB/BASk/vTaSgkQIECAAAECBAgQGCMgII0BspsA\nAQIECBAgQIAAgf4ICEj96bWVEiBAgAABAgQIECAwRkBAGgNkNwECBAgQIECAAAEC/REQkPrT\nayslQIAAAQIECBAgQGCMgIA0BshuAgQIECBAgAABAgT6IyAg9afXVkqAAAECBAgQIECAwBgB\nAWkMkN0ECBAgQIAAAQIECPRHQEDqT6+tlAABAgQIECBAgACBMQIC0hgguwkQIECAAAECBAgQ\n6I+AgNSfXlspAQIECBAgQIAAAQJjBASkMUB2EyBAgAABAgQIECDQHwEBqT+9tlICBAgQIECA\nAAECBMYICEhjgOwmQIAAAQIECBAgQKA/AgJSf3ptpQQIECBAgAABAgQIjBEQkMYA2U2AAAEC\nBAgQIECAQH8EBKT+9NpKCRAgQIAAAQIECBAYIyAgjQGymwABAgQIECBAgACB/ggISP3ptZUS\nIECAAAECBAgQIDBGQEAaA2Q3AQIECBAgQIAAAQL9ERCQ+tNrKyVAgAABAgQIECBAYIyAgDQG\nyG4CBAgQIECAAAECBPojICD1p9dWSoAAAQIECBAgQIDAGAEBaQyQ3QQIECBAgAABAgQI9EdA\nQOpPr62UAAECBAgQIECAAIExAgLSGCC7CRAgQIAAAQIECBDoj4CA1J9eWykBAgQIECBAgAAB\nAmMEBKQxQHYTIECAAAECBAgQINAfAQGpP722UgIECBAgQIAAAQIExggISGOA7CZAgAABAgQI\nECBAoD8CAlJ/em2lBAgQIECAAAECBAiMERCQxgDZTYAAAQIECBAgQIBAfwQEpP702koJECBA\ngAABAgQIEBgjICCNAbKbAAECBAgQIECAAIH+CAhI/em1lRIgQIAAAQIECBAgMEZAQBoDZDcB\nAgQIECBAgAABAv0REJD602srJUCAAAECBAgQIEBgjICANAbIbgIECBAgQIAAAQIE+iMgIPWn\n11ZKgAABAgQIECBAgMAYAQFpDJDdBAgQIECAAAECBAj0R0BA6k+vrZQAAQIECBAgQIAAgTEC\nAtIYILsJECBAgAABAgQIEOiPgIDUn15bKQECBAgQIECAAAECYwQEpDFAdhMgQIAAAQIECBAg\n0B8BAak/vbZSAgQIECBAgAABAgTGCAhIY4DsJkCAAAECBAgQIECgPwICUn96baUECBAgQIAA\nAQIECIwREJDGANlNgAABAgQIECBAgEB/BASk/vTaSgkQIECAAAECBAgQGCMgII0BspsAAQIE\nCBAgQIAAgf4ICEj96bWVEiBAgAABAgQIECAwRkBAGgNkNwECBAgQIECAAAEC/REQkPrTaysl\nQIAAAQIECBAgQGCMgIA0BshuAgQIECBAgAABAgT6IyAg9afXVkqAAAECBAgQIECAwBgBAWkM\nkN0ECBAgQIAAAQIECPRHQEDqT6+tlAABAgQIECBAgACBMQIC0hgguwkQIECAAAECBAgQ6I+A\ngNSfXlspAQIECBAgQIAAAQJjBASkMUB2EyBAgAABAgQIECDQHwEBqT+9tlICBAgQIECAAAEC\nBMYICEhjgOwmQIAAAQIECBAgQKA/AgJSf3ptpQQIECBAgAABAgQIjBEQkMYA2U2AAAECBAgQ\nIECAQH8EBKT+9NpKCRAgQIAAAQIECBAYIyAgjQGymwABAgQIECBAgACB/ggISP3ptZUSIECA\nAAECBAgQIDBGQEAaA2Q3AQIECBAgQIAAAQL9EZirfKk7xvreFLVL1I1RD0SNGtvEjkOi9oi6\nJequKIMAAQIECBAgQIAAgR4J1ByQ/mX08cKo3eb185vx/JejHpq3LZ/uHfWFqH3zxWDcGo9H\nRN073OCRAAECBAgQIECAAIG6BWr9it3h0bbLox6POjHqZ6N+L+qgqK9HbRs1HLPx5LKoPaOO\nicqwlOe8NuqGqB2iDAIECBAgQIAAAQIEeiBQ6ydIZ0Tv8itz74/674M+fjsefzrq2KgMUF+O\nynFS1GGDxytyQ4y7Nz/MXBKPR0ddPHjtgQABAgQIECBAgACBigVq/QTp89Gzj0Z9cUHvvjp4\nvd+87cfG8+eirpy3LZ/m63VRJ+QLgwABAgQIECBAgACB+gVq/QTpPy/Suvwq3XsG268bPK6M\nxwOj7ojKr+PNH0/Gi9ujDojK416IMggQIECAAAECBAgQqFig1oA0v2X7x4ujov5ZVIad34n6\nTlSOvLvdqqhH88UiY21sy3C0e9T9i+wftSlvDPHxqHzvScYrJjnIMQQIECBAgAABAgQITFeg\nDwEpf4f0vgFj/rboS/NIdxo8f2TetvlPMyDlWO6NGvLTpoejJg1ItX7VMe0MAgQIECBAgAAB\nAp0R6ENA+nB040NR7446Nepvok6Jyhsw5G+McowKKHmjhxwbNj9M/Ncn4sgPTHz0zMxb4tgj\nl3G8QwkQIECAAAECBAgQmILAqGAwhUtttbf8Xlz5+1EZiPKrdhkKMyjleDBqU9Su+WKRMdye\ngccgQIAAAQIECBAgQKBygT4EpPktzN8e3Rj1j6J+Kmp9VP6hscMgFE+3GLn9maiFN3DY4iAv\nCBAgQIAAAQIECBCoQ6DGgPTyaE3+1mh4S++Fndo42PD04PG2eMwbOeSNFeaPvDHDflE3Ry33\nK3bz38dzAgQIECBAgAABAgQ6IlBjQMrgk1+J+8dRBy3oQ/7W55Cov40a3oDhonieX7s7Lmr+\nOD5e5PYL52/0nAABAgQIECBAgACBegUyANQ4TotFfS0q71j36ahro94UdXZUfq1ufhi6Jl7n\np0jnRe0YdX3U6qgzo66OuirKIECAAAECBAgQIECgBwI1foKUbbsh6p1R+SnRGVFfifpo1K1R\nb476VtRw5FfuDo/KEHVW1JcHj3nOyVEGAQIECBAgQIAAAQI9Eaj1E6RsXwacfaP2jPrJqLui\nRt1sIf8cpAxU+QnSPlH3ReUd7gwCBAgQIECAAAECBHokUHNAGrYxw07WJOOpOChvymAQIECA\nAAECBAgQINBDgVq/YtfDVloyAQIECBAgQIAAAQKlAgJSqaDzCRAgQIAAAQIECBCoRkBAqqaV\nFkKAAAECBAgQIECAQKmAgFQq6HwCBAgQIECAAAECBKoREJCqaaWFECBAgAABAgQIECBQKiAg\nlQo6nwABAgQIECBAgACBagQEpGpaaSEECBAgQIAAAQIECJQKCEilgs4nQIAAAQIECBAgQKAa\nAQGpmlZaCAECBAgQIECAAAECpQICUqmg8wkQIECAAAECBAgQqEZAQKqmlRZCgAABAgQIECBA\ngECpgIBUKuh8AgQIECBAgAABAgSqERCQqmmlhRAgQIAAAQIECBAgUCogIJUKOp8AAQIECBAg\nQIAAgWoEBKRqWmkhBAgQIECAAAECBAiUCghIpYLOJ0CAAAECBAgQIECgGgEBqZpWWggBAgQI\nECBAgAABAqUCAlKpoPMJECBAgAABAgQIEKhGQECqppUWQoAAAQIECBAgQIBAqYCAVCrofAIE\nCBAgQIAAAQIEqhEQkKpppYUQIECAAAECBAgQIFAqICCVCjqfAAECBAgQIECAAIFqBASkalpp\nIQQIECBAgAABAgQIlAoISKWCzidAgAABAgQIECBAoBoBAamaVloIAQIECBAgQIAAAQKlAgJS\nqaDzCRAgQIAAAQIECBCoRkBAqqaVFkKAAAECBAgQIECAQKmAgFQq6HwCBAgQIECAAAECBKoR\nEJCqaaWFECBAgAABAgQIECBQKiAglQo6nwABAgQIECBAgACBagQEpGpaaSEECBAgQIAAAQIE\nCJQKCEilgs4nQIAAAQIECBAgQKAaAQGpmlZaCAECBAgQIECAAAECpQICUqmg8wkQIECAAAEC\nBAgQqEZAQKqmlRZCgAABAgQIECBAgECpgIBUKuh8AgQIECBAgAABAgSqERCQqmmlhRAgQIAA\nAQIECBAgUCogIJUKOp8AAQIECBAgQIAAgWoEBKRqWmkhBAgQIECAAAECBAiUCghIpYLOJ0CA\nAAECBAgQIECgGgEBqZpWWggBAgQIECBAgAABAqUCAlKpoPMJECBAgAABAgQIEKhGQECqppUW\nQoAAAQIECBAgQIBAqYCAVCrofAIECBAgQIAAAQIEqhEQkKpppYUQIECAAAECBAgQIFAqICCV\nCjqfAAECBAgQIECAAIFqBASkalppIQQIECBAgAABAgQIlAoISKWCzidAgAABAgQIECBAoBoB\nAamaVloIAQIECBAgQIAAAQKlAgJSqaDzCRAgQIAAAQIECBCoRkBAqqaVFkKAAAECBAgQIECA\nQKmAgFQq6HwCBAgQIECAAAECBKoREJCqaaWFECBAgAABAgQIECBQKiAglQo6nwABAgQIECBA\ngACBagQEpGpaaSEECBAgQIAAAQIECJQKCEilgs4nQIAAAQIECBAgQKAaAQGpmlZaCAECBAgQ\nIECAAAECpQICUqmg8wkQIECAAAECBAgQqEZAQKqmlRZCgAABAgQIECBAgECpgIBUKuh8AgQI\nECBAgAABAgSqERCQqmmlhRAgQIAAAQIECBAgUCogIJUKOp8AAQIECBAgQIAAgWoEBKRqWmkh\nBAgQIECAAAECBAiUCghIpYLOJ0CAAAECBAgQIECgGgEBqZpWWggBAgQIECBAgAABAqUCAlKp\noPMJECBAgAABAgQIEKhGQECqppUWQoAAAQIECBAgQIBAqYCAVCrofAIECBAgQIAAAQIEqhEQ\nkKpppYUQIECAAAECBAgQIFAqICCVCjqfAAECBAgQIECAAIFqBASkalppIQQIECBAgAABAgQI\nlArMlb5By89/WczvZ6P+QdR9Ud+OeiJqsbFNbDwkao+oW6LuijIIECBAgAABAgQIEOiRQM0B\n6deij+dHvXJeP5+K52dHXThvWz7dO+oLUfvmi8G4NR6PiLp3uMEjAQIECBAgQIAAAQJ1C9T6\nFbt3RNs+E/VM1O9G5adIp0XdH/WJqGOihmM2nlwWtWdUbs+wdGLUa6NuiNohyiBAgAABAgQI\nECBAoAcCtX6ClKEog89vRl076GN+ve6bUTdFfTDq8qgcJ0UdNni8IjfEuHvzw8wl8Xh01MWD\n1x4IECBAgAABAgQIEKhYoMZPkHJN+alPfkXuugW9++t4fUfU66PyN0c5jo16LurKqPkjX6+L\nOmH+Rs8JECBAgAABAgQIEKhXoMZPkDZGu948omXbxfa8CcPfRW2IWhl1YFSGpsej5o8n48Xt\nUQdE5XEvRBkECBAgQIAAAQIECFQsUGNAWqpd/y527hT1ycFBu8TjqqhHB68XPqyNDRmOdo/K\n3y9NOvITrN+KynMnGa+Z5CDHECBAgAABAgQIECAwXYE+BaRfCcp/H5W37/69qBwZlnI8svnh\nR/6aASnHcm/UkO/7tqgMX5OMHSc5yDEECBAgQIAAAQIECExXoC8B6dhgzBsuPBz17qhno3Lk\nb4xyjPot1vB3Svl1vOWMB+LgdyzjhLfEsd9YxvEOJUCAAAECBAgQIEBgCgKjgsEULrXV3jI/\nNfp01PeiDo+6LWo4Hownm6J2HW5Y8DjcPuoPl11wuJcECBAgQIAAAQIECHRZoOZPkPI23x+P\nyt8C5d3r3hX1/aj5Y328eChqGITm78vnuT3/LKWFN3DIfQYBAgQIECBAgAABApUJ1PoJUq7r\nU1EZjq6JWh21MBzFph+O/ERp/6jdNr988a95Y4b9om6OWu5X7F58E08IECBAgAABAgQIEOiO\nQK0B6TejBcdGXR313qj8FGjUuCh25Cdpxy044PjB9gsXbPeSAAECBAgQIECAAIFKBWr8it0r\nolfnDvr1E/H4ZyN6d3RsfzoqP2HKT5HOi8q7yV0ftTrqzKgMWFdFGQQIECBAgAABAgQI9ECg\nxoD0i9G3nQe9e9sSPRz+GUUb45i8ecPlUWdFnR2V49qok3/4zF8IECBAgAABAgQIEOiFQI0B\n6fPRubxBw3JG/jlI74zKT5D2ibovKu9wZxAgQIAAAQIECBAg0COBGgNSSfueipPzpgwGAQIE\nCBAgQIAAAQI9FKj1Jg09bKUlEyBAgAABAgQIECBQKiAglQo6nwABAgQIECBAgACBagQEpGpa\naSEECBAgQIAAAQIECJQKCEilgs4nQIAAAQIECBAgQKAaAQGpmlZaCAECBAgQIECAAAECpQIC\nUqmg8wkQIECAAAECBAgQqEZAQKqmlRZCgAABAgQIECBAgECpgIBUKuh8AgQIECBAgAABAgSq\nERCQqmmlhRAgQIAAAQIECBAgUCogIJUKOp8AAQIECBAgQIAAgWoEBKRqWmkhBAgQIECAAAEC\nBAiUCghIpYLOJ0CAAAECBAgQIECgGgEBqZpWWggBAgQIECBAgAABAqUCAlKpoPMJECBAgAAB\nAgQIEKhGQECqppUWQoAAAQIECBAgQIBAqYCAVCrofAIECBAgQIAAAQIEqhEQkKpppYUQIECA\nAAECBAgQIFAqICCVCjqfAAECBAgQIECAAIFqBOaqWYmFENhSYJd4eeCWmzr56sGY9W2dnLlJ\nEyBAgAABAgQ6KCAgdbBppjyRwBlx1AejNk10dDsPml2xYsVjGzdu3LWd0zMrAgQIECBAgEB9\nAgJSfT21os0CKw866KDnzznnnFVdBVmzZs3M+eefv7Kr8zdvAgQIECBAgEAXBfwGqYtdM2cC\nBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBN\nhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQ\nRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECA\nAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBA\ngAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtd\nM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYi\nICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQI\nECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQ\nIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWb\nEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEB\nqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAEC\nBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAAB\nAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cC\nBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBN\nhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQ\nRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECA\nAAECBKYiICBNhdWbEiBAgAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBA\ngAABAgQIECDQRQEBqYtdM2cCBAgQIECAAAECBKYiICBNhdWbEiBAgAABAgQIECDQRYE+BaRf\njga9YYkmbRP7Do06MmrvJY6ziwABAgQIECBAgACBSgX6EpDeF/27OuqIEX3MQPTtqK9HXRV1\nZ9R3ovaKMggQIECAAAECBAgQ6IlAHwLSu6OXf7REP2dj32VRe0YdE5Vh6cSo10bdELVDlEGA\nAAECBAgQIECAQA8E5ipe4ytibZ+I+tWo55ZY50mx77CofLxicNzdg8dL4vHoqIsHrz0QIECA\nAAECBAgQIFCxQM2fIH0x+pbh6HNR+YnQqHFs7MgAdeWCA/L1uqgTFmz3kgABAgQIECBAgACB\nSgVqDkg3R8/eEfUrUY+P6N/K2H5gVP7maOExT8a226MOiMrjDAIECBAgQIAAAQIEKheo+St2\nJ0/Qu13imFVRj444dm1sz3C0e9T9I45ZbHPeEe+XovK9Jxn7THKQYwgQIECAAAECBAgQmK5A\nzQFpErmdBgc9MuLgDEg5lnujhp+Kc/L3S5N+8tT3PqSxQYAAAQIECBAgQGCrC/T9X8zzN0Y5\nRn3VMD8JyrFh88PEf70njtxj4qNnZt4Sx35jGcc7lAABAgQIECBAgACBKQiMCgZTuFQr3/LB\nmNWmqF1HzG64/YkR+20mQIAAAQIECBAgQKAigb4HpPXRy4eihkFoYWtz+zNRC2/gsPA4rwkQ\nIECAAAECBAgQqECg7wEpW3hb1P5Ru+WLeSNvzLBfVN4Nb7lfsZv3Np4SIECAAAECBAgQINAV\nAQFpZuaiaFb+Fuu4BU07frD9wgXbvSRAgAABAgQIECBAoFKBvt+kIdt6TVR+inRe1I5R10et\njjoz6uqoq6IMAgQIECBAgAABAgR6ICAgzcxsjD4fHnV51FlRZ0fluDZqkj9L6YcHl//lDfEW\na941M/Py/F3UlMa/2evhh3eeufHGV0/p/af/tvfc88aZDRuO3G5m5k/evfTVTn/dE09smu3y\nWu+8c7+ZTZveE3dS/NyYtS4tYS8BAgQIECBAoAGBu2dmZr/TwHWmfonZqV+hWxfIT5DyD229\nLyrvcNfUiNt8XxC3+f7tKd8t79ntt9lmw6ptt922qXW95NdZv379zPPPr49Qu+NTS7/5uu1W\nrFi/arvttu3s3+MbNmyYee655+Muizs9ufRa7SVAgAABAgQIbHWBSyMgnb7VZ/ESTKCz//L4\nEqy9TW8x/HOQMrk8P8WJfeatb33rr5922mlTvMR03/raa6+dufTSS7/3/PPP7zXmShccdNBB\np55zzjmrxhzX2t1r1qyZOf/885+OoJTB3SBAgAABAgQIEGhAwE0aGkB2CQIECBAgQIAAAQIE\nuiEgIHWjT2ZJgAABAgQIECBAgEADAgJSA8guQYAAAQIECBAgQIBANwQEpG70ySwJECBAgAAB\nAgQIEGhAQEBqANklCBAgQIAAAQIECBDohoCA1I0+mSUBAgQIECBAgAABAg0ICEgNILsEAQIE\nCBAgQIAAAQLdEBCQutEnsyRAgAABAgQIECBAoAEBAakBZJcgQIAAAQIECBAgQKAbAgJSN/pk\nlgQIECBAgAABAgQINCAgIDWA7BIECBAgQIAAAQIECHRDQEDqRp/MkgABAgQIECBAgACBBgQE\npAaQXYIAAQIECBAgQIAAgW4ICEjd6JNZEiBAgAABAgQIECDQgICA1ACySxAgQIAAAQIECBAg\n0A0BAakbfTJLAgQIECBAgAABAgQaEJhr4BouQYDAdAXyP3TsNd1LNPLuT8dVHm3kSi5CgAAB\nAgQIEBghICCNgLGZQIcETom5Xtih+S461dnZ2XWbNm16WezctOgBNhIgQIAAAQIEGhAQkBpA\ndgkCUxbYYa+99lp39tlnbzfl60zt7e+6666ZCy64IOc/GyUgTU3aGxMgQIAAAQLjBASkcUL2\nE+iAwNzc3KZXvepVHZjp4lN85JFHFt9hKwECBAgQIECgYQE3aWgY3OUIECBAgAABAgQIEGiv\ngIDU3t6YGQECBAgQIECAAAECDQsISA2DuxwBAgQIECBAgAABAu0VEJDa2xszI0CAAAECBAgQ\nIECgYQEBqWFwlyNAgAABAgQIECBAoL0CAlJ7e2NmBAgQIECAAAECBAg0LCAgNQzucgQIECBA\ngAABAgQItFdAQGpvb8yMAAECBAgQIECAAIGGBQSkhsFdjgABAgQIECBAgACB9goISO3tjZkR\nIECAAAECBAgQINCwgIDUMLjLESBAgAABAgQIECDQXgEBqb29MTMCBAgQIECAAAECBBoWEJAa\nBnc5AgQIECBAgAABAgTaKyAgtbc3ZkaAAAECBAgQIECAQMMCAlLD4C5HgAABAgTD8aYXAAAP\nUklEQVQIECBAgEB7BQSk9vbGzAgQIECAAAECBAgQaFhAQGoY3OUIECBAgAABAgQIEGivgIDU\n3t6YGQECBAgQIECAAAECDQsISA2DuxwBAgQIECBAgAABAu0VEJDa2xszI0CAAAECBAgQIECg\nYQEBqWFwlyNAgAABAgQIECBAoL0CAlJ7e2NmBAgQIECAAAECBAg0LCAgNQzucgQIECBAgAAB\nAgQItFdAQGpvb8yMAAECBAgQIECAAIGGBQSkhsFdjgABAgQIECBAgACB9goISO3tjZkRIECA\nAAECBAgQINCwgIDUMLjLESBAgAABAgQIECDQXgEBqb29MTMCBAgQIECAAAECBBoWEJAaBnc5\nAgQIECBAgAABAgTaKyAgtbc3ZkaAAAECBAgQIECAQMMCcw1fz+UIECBQIvC2ubm5P16xYsU2\nJW+ytc/duHHj4+vXrz845vHs1p6L6xMgQIAAAQJbCghIW3p4RYBAuwVet+22277yuOOOW9Xu\naY6e3dq1a2c++9nP7hFH7BglII2msocAAQIECGwVAQFpq7C7KAECP6bApu23337D29/+9h/z\n9K1/2r333psBaetPxAwIECBAgACBRQX8BmlRFhsJECBAgAABAgQIEOijgIDUx65bMwECBAgQ\nIECAAAECiwoISIuy2EiAAAECBAgQIECAQB8FBKQ+dt2aCRAgQIAAAQIECBBYVEBAWpTFRgIE\nCBAgQIAAAQIE+iggIPWx69ZMgAABAgQIECBAgMCiAgLSoiw2EiBAgAABAgQIECDQRwEBqY9d\nt2YCBAgQIECAAAECBBYVEJAWZbGRAAECBAgQIECAAIE+Csz1cdHWTIAAgQ4IvCbmeFbUNh2Y\n61JTfDZ2nhn1zFIH2UeAAAECBNoiICC1pRPmQYAAgS0Ffn7FihUnHnrooVtu7dCrF154YebG\nG2/Mbyp8Muq2Dk3dVAkQIECgxwICUo+bb+kECLRbYNWqVetPP/30Ve2e5ejZPf744xmQRh9g\nDwECBAgQaKGA3yC1sCmmRIAAAQIECBAgQIDA1hEQkLaOu6sSIECAAAECBAgQINBCAQGphU0x\nJQIECBAgQIAAAQIEto6AgLR13F2VAAECBAgQIECAAIEWCghILWyKKREgQIAAAQIECBAgsHUE\n3MVu67i7KgECBAhsKbBbvFy55abOvXohZvxI52ZtwgQIECCwhYCA9P858g9jPCRqj6hbou6K\nMggQIEBg+gIHxSX+ZvqXaeQKb4qrfGuJK20f+34/arsljunCro0xyY9E3d+FyZojAQIEliMg\nIG3W2jsevhC17zy8W+P5EVH3ztvmKQECBAi89AIvz7e86KKLZuIPx33p372Bd9y4cePMqaee\nmlf64VqWuORPx77fPvjgg9evXNndD8xuuummFbHmr8Varl5irXYRIECgkwIC0szMbHTusqg9\no46JWhP11qhPRN0QtX/UD6IMAgQIEJiiwJ577tnpgLQcmghTczvvvPNyTmnVsUcdddTz69at\na9WcTIYAAQIvlYCANDNzUmAeFpWPVwxg7x48XhKPR0ddPHjtgQABAgQIEJhc4Kfi0HGfqk3+\nblvnyPw64Z1R+WgQINADAQFpZubY6PNzUVcu6He+vjDqhCgBaQGOlwQIECBAYIxAfkR2T1Q3\nvze55eLyGybD/4i65R6vCBCoTqDvASm/AH5g1B1Rjy/o7pPx+vaoA6LyuLw7kUGAAAECBAhM\nJrAqDltx7rnnzuTXJ7s6PvCBD6xbu3btdl2dv3kTILB8gb4HpF2CLP8B/ugIurWxPcPR7lHL\nvVPPPxycGw9jR34FoZHxzDPPzNx3332NXGsaF3nssccmftv4fvxsl9f66KOj/rb8UYIXXnih\n02t95JGJ74w8u2HDhk6v9fvf//6PNnDElvgRfKfX+uST+d+ZJh/5v9cu36Rh8pXOzDzwwAMz\nP/hBd3/emn9vTrre/P+dp59+etLDW3fcpk2bJppT/L3793Fg3q6+0yN6e2IsYNynZXnX3+6m\n3s0dysZ+M+rBzS9H/jX/HW2PkXu7syO/Jjr5v0R1Z11mOgWBn4n3zP+BfG7Ee+f23L/3iP2j\nNg/fN8+dtPK7zXmr8WmOi+LNJ51Pa4+bm5u7ZQKkc2pYa/wf7iRp9pQa1jo7O5v/tjjuX7r+\nRQ1rjTXkJ9I7RS01/knsbO3/Dpcxtw1x7Lj/CJS3+a5hrbmG/FbCUiMt0qSG9ebfo0uN/Hs8\n/16vYa35z56lRvwj7If/DKthrfn/KUuOWOvfxQE1rPXsJRe6eeeaStZ6wQRrdchAYNy/jNQO\n9ZpYYN7G+8+jjlxksbn9PVGvi/ruIvuX2vSK2JmfPk06MiA9NOnBP+Zxc3Fe5//rVqwh/7P0\nM2MMMmzmWrv+93j+Z9espUau8ZVRXV9r9nSSjxxyrV3/TcOzsYYnosaN/PR62v/hZNwcSvfn\nbzwn+a+Wy/1nZum8pnF+hoFJPvrNby9sO40JNPieGfIenuB6PxHH5J/91OUx6f8/ZyB8WZcX\nGnPP0JP/LpKPS4288UbXb76Ra8yvL+Tfy0uN7Gn2tusj17q+64sw/2YEMjDkP/i+NuJyfxXb\n839A+X/cBgECBAgQIECAAAEClQt0/b/ClrYnk3T+l5JdR7xRbs//qr3wBg4jDreZAAECBAgQ\nIECAAAEC3RbIT4/yaxELv3qWX23J7f8zyiBAgAABAgQIECBAgEAvBP55rDK/RnfGgtV+cLD9\nvQu2e0mAAAECBAgQIECAAIFqBfJrhrdG5Y/0fj8q78rzB4PXeZMGgwABAgQIECBAgAABAr0S\nyK/X/WVU3rAhP03K+lLUq6MMAgQIECBAgAABAgQI9FJgx1j1wVGCUS/bb9EECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE\nCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUCrw/wD10j34Kyz7FgAAAABJRU5ErkJg\ngg==",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"barplot(ptau,las=2)\n",
"abline(h=sum(ptau)/11,col=\"blue\")\n",
"cat(\"\\nAltura linea azul = promedio de los taus\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Primer plano factorial del ACM de frecuencia de lectura de niños, mostrando las categorías activas"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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TM1KSBFFpCXmtkVhXsl8pkkZq03gqH6uoVr5pmYkhSNo3hD4qvpKymygF6LmtZA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QaEcE+MiStgKr7iOPPNKOTVSbhIAQEAJC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dZbb3l9KFIoeNRLO8GAX5SfF154IT0euneI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\nAAAAAElFTkSuQmCC",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plot(acm,Trow=FALSE,gg=TRUE,xlim=c(-1,1),ylim=c(-1,1.3),cframe=1.1,col.col=\"black\",cex.global=0.8)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Primer eje factorial\n",
"\n",
"Para observar simultáneamente, las oposiciones de las categorías en el eje se incluye el signo de la coordenada (aquí está entre paréntesis). \n",
"El primer eje factorial contrapone: ir a teatro al menos una vez al año (-) contra no ir (+), leer libros diariamente (-) contra no leer (+), ir a cine mensualmente (-) contra no ir (+), ver videos diariamente (-), contra no ver (+), escuchar radio diariamente (-) contra no escuchar (+) y escuchar música grabada diariamente (-) contra no escuchar (+). Es decir, separa a los niños de mayor consumo cultural, al lado negativo, de los que no tiene consumo cultural, al lado positivo. Entonces el primer eje es un indicador de consumo cultural y ordena a los niños: al lado negativo los que más consumen, al lado positivo los que no consumen.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Segundo eje factorial\n",
"\n",
"El segundo eje contrapone valores medios contra valores extremos en algunas variables, lo que indica que hay presencia de efecto Guttman: leer varias veces a la semana contra no leer o hacerlo diariamente, ver videos varias veces a la semana contra no ver o hacerlo diariamente, escuchar radio varios días a la semana contra hacerlo diariamente y escuchar música grabada varios días a la semana contra escucharla diariamente o no hacerlo. \n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Tercer eje factorial\n",
"\n",
"El tercer eje separa algunas categorías intermedias: ver videos varios días a la semana contra hacerlo semanal o mensualmente, escuchar radio varias veces a la semana contra hacerlo semanalmente; y escuchar música grabada varios días a la semana contra semanalmente. \n",
"\n",
"Aunque el tercer eje permite ver algunas diferencias, mejor que en los dos primeros ejes, se puede prescindir de este en una síntesis del consumo cultural de los niños.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Primer plano factorial\n",
" Se observa claramente el efecto Gutttman (forma de parábola en las variables ordinales) en todas las variables, es decir, las categorías están ordenadas: arriba a la derecha están las que indican que no hay consumo; a medida que se desciende en dirección a la izquierda, el consumo cultural va aumentando; luego arriba a la izquierda se ubican las categorías de mayor consumo cultural. \n",
" \n",
"Como las categorías se ubican en el promedio de las coordenadas de los niños que las asumen (alejado por el inverso de la raíz del valor propio), los niños quedan ordenados de la misma forma, según su consumo cultural. "
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"categoría | peso | coordenadas | cont.absoluta | coseno cuadrado"
]
},
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 31 × 10</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>peso</th><th scope=col>Comp1</th><th scope=col>Comp2</th><th scope=col>Comp3</th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Axis3</th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Axis3</th></tr>\n",
"\t<tr><th></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>Teat.sema</th><td>0.0049</td><td>-0.4980</td><td>-0.0758</td><td>-0.3073</td><td>0.0040</td><td>0.0001</td><td>0.0022</td><td>0.0075</td><td>0.0002</td><td>0.0029</td></tr>\n",
"\t<tr><th scope=row>Teat.mens</th><td>0.0071</td><td>-0.9211</td><td> 0.5228</td><td> 0.2842</td><td>0.0200</td><td>0.0084</td><td>0.0027</td><td>0.0378</td><td>0.0122</td><td>0.0036</td></tr>\n",
"\t<tr><th scope=row>Teat.trim</th><td>0.0110</td><td>-0.8722</td><td>-0.5595</td><td>-0.2800</td><td>0.0278</td><td>0.0148</td><td>0.0041</td><td>0.0537</td><td>0.0221</td><td>0.0055</td></tr>\n",
"\t<tr><th scope=row>Teat.seme</th><td>0.0090</td><td>-0.9047</td><td>-0.3679</td><td>-0.5120</td><td>0.0246</td><td>0.0053</td><td>0.0114</td><td>0.0470</td><td>0.0078</td><td>0.0150</td></tr>\n",
"\t<tr><th scope=row>Teat.anua</th><td>0.0137</td><td>-0.9318</td><td> 0.1107</td><td> 0.0765</td><td>0.0396</td><td>0.0007</td><td>0.0004</td><td>0.0778</td><td>0.0011</td><td>0.0005</td></tr>\n",
"\t<tr><th scope=row>Teat.no</th><td>0.1209</td><td> 0.3269</td><td> 0.0382</td><td> 0.0509</td><td>0.0430</td><td>0.0008</td><td>0.0015</td><td>0.2824</td><td>0.0039</td><td>0.0068</td></tr>\n",
"\t<tr><th scope=row>Libr.diar</th><td>0.0274</td><td>-0.8469</td><td> 0.7776</td><td>-0.1125</td><td>0.0654</td><td>0.0713</td><td>0.0017</td><td>0.1411</td><td>0.1190</td><td>0.0025</td></tr>\n",
"\t<tr><th scope=row>Libr.vdse</th><td>0.0509</td><td>-0.0674</td><td>-0.4345</td><td> 0.3652</td><td>0.0008</td><td>0.0414</td><td>0.0325</td><td>0.0020</td><td>0.0830</td><td>0.0587</td></tr>\n",
"\t<tr><th scope=row>Libr.sema</th><td>0.0257</td><td> 0.0215</td><td>-0.4822</td><td>-0.3068</td><td>0.0000</td><td>0.0257</td><td>0.0116</td><td>0.0001</td><td>0.0424</td><td>0.0172</td></tr>\n",
"\t<tr><th scope=row>Libr.mens</th><td>0.0109</td><td>-0.5762</td><td>-0.2536</td><td>-0.6726</td><td>0.0120</td><td>0.0030</td><td>0.0236</td><td>0.0233</td><td>0.0045</td><td>0.0317</td></tr>\n",
"\t<tr><th scope=row>Libr.trim</th><td>0.0069</td><td> 0.4624</td><td> 0.0360</td><td>-0.1619</td><td>0.0049</td><td>0.0000</td><td>0.0009</td><td>0.0093</td><td>0.0001</td><td>0.0011</td></tr>\n",
"\t<tr><th scope=row>Libr.anua</th><td>0.0047</td><td>-0.0670</td><td>-0.8887</td><td>-0.1619</td><td>0.0001</td><td>0.0158</td><td>0.0006</td><td>0.0001</td><td>0.0227</td><td>0.0008</td></tr>\n",
"\t<tr><th scope=row>Libr.no</th><td>0.0402</td><td> 0.7338</td><td> 0.4944</td><td> 0.0396</td><td>0.0719</td><td>0.0423</td><td>0.0003</td><td>0.1710</td><td>0.0776</td><td>0.0005</td></tr>\n",
"\t<tr><th scope=row>Cine.mens</th><td>0.0147</td><td>-0.9917</td><td>-0.0014</td><td> 0.8793</td><td>0.0481</td><td>0.0000</td><td>0.0545</td><td>0.0952</td><td>0.0000</td><td>0.0749</td></tr>\n",
"\t<tr><th scope=row>Cine.trim</th><td>0.0175</td><td>-0.7231</td><td> 0.1767</td><td>-0.3836</td><td>0.0304</td><td>0.0024</td><td>0.0123</td><td>0.0614</td><td>0.0037</td><td>0.0173</td></tr>\n",
"\t<tr><th scope=row>Cine.seme</th><td>0.0123</td><td>-0.3904</td><td>-0.5121</td><td>-0.3316</td><td>0.0062</td><td>0.0138</td><td>0.0065</td><td>0.0121</td><td>0.0208</td><td>0.0087</td></tr>\n",
"\t<tr><th scope=row>Cine.anua</th><td>0.0139</td><td>-0.2499</td><td> 0.1000</td><td>-0.1008</td><td>0.0029</td><td>0.0006</td><td>0.0007</td><td>0.0057</td><td>0.0009</td><td>0.0009</td></tr>\n",
"\t<tr><th scope=row>Cine.no</th><td>0.1083</td><td> 0.3277</td><td> 0.0168</td><td>-0.0070</td><td>0.0387</td><td>0.0001</td><td>0.0000</td><td>0.1994</td><td>0.0005</td><td>0.0001</td></tr>\n",
"\t<tr><th scope=row>Vide.diar</th><td>0.0192</td><td>-1.0668</td><td> 1.2352</td><td> 0.3794</td><td>0.0727</td><td>0.1261</td><td>0.0132</td><td>0.1481</td><td>0.1986</td><td>0.0187</td></tr>\n",
"\t<tr><th scope=row>Vide.vdse</th><td>0.0605</td><td>-0.2837</td><td>-0.5046</td><td> 0.5419</td><td>0.0162</td><td>0.0663</td><td>0.0850</td><td>0.0458</td><td>0.1449</td><td>0.1672</td></tr>\n",
"\t<tr><th scope=row>Vide.sema</th><td>0.0342</td><td>-0.1487</td><td>-0.3900</td><td>-0.8224</td><td>0.0025</td><td>0.0224</td><td>0.1106</td><td>0.0057</td><td>0.0392</td><td>0.1744</td></tr>\n",
"\t<tr><th scope=row>Vide.mens</th><td>0.0083</td><td>-0.0903</td><td> 0.0105</td><td>-1.4645</td><td>0.0002</td><td>0.0000</td><td>0.0851</td><td>0.0004</td><td>0.0000</td><td>0.1122</td></tr>\n",
"\t<tr><th scope=row>Vide.no</th><td>0.0446</td><td> 0.9752</td><td> 0.4495</td><td> 0.0041</td><td>0.1409</td><td>0.0388</td><td>0.0000</td><td>0.3471</td><td>0.0738</td><td>0.0000</td></tr>\n",
"\t<tr><th scope=row>Radi.diar</th><td>0.0329</td><td>-0.7241</td><td> 0.7093</td><td>-0.1031</td><td>0.0574</td><td>0.0712</td><td>0.0017</td><td>0.1289</td><td>0.1237</td><td>0.0026</td></tr>\n",
"\t<tr><th scope=row>Radi.vdse</th><td>0.0333</td><td>-0.0867</td><td>-0.7197</td><td> 0.4753</td><td>0.0008</td><td>0.0743</td><td>0.0360</td><td>0.0019</td><td>0.1294</td><td>0.0564</td></tr>\n",
"\t<tr><th scope=row>Radi.sema</th><td>0.0084</td><td>-0.3519</td><td>-0.6191</td><td>-1.8668</td><td>0.0034</td><td>0.0138</td><td>0.1396</td><td>0.0065</td><td>0.0203</td><td>0.1843</td></tr>\n",
"\t<tr><th scope=row>Radi.no</th><td>0.0921</td><td> 0.3220</td><td> 0.0633</td><td> 0.0346</td><td>0.0318</td><td>0.0016</td><td>0.0005</td><td>0.1280</td><td>0.0049</td><td>0.0015</td></tr>\n",
"\t<tr><th scope=row>Musi.diar</th><td>0.0270</td><td>-1.0375</td><td> 1.0668</td><td> 0.2862</td><td>0.0966</td><td>0.1322</td><td>0.0106</td><td>0.2079</td><td>0.2198</td><td>0.0158</td></tr>\n",
"\t<tr><th scope=row>Musi.vdse</th><td>0.0594</td><td>-0.2193</td><td>-0.7871</td><td> 0.4429</td><td>0.0095</td><td>0.1585</td><td>0.0558</td><td>0.0267</td><td>0.3435</td><td>0.1088</td></tr>\n",
"\t<tr><th scope=row>Musi.sema</th><td>0.0132</td><td>-0.5368</td><td>-0.4506</td><td>-2.1512</td><td>0.0126</td><td>0.0115</td><td>0.2922</td><td>0.0248</td><td>0.0175</td><td>0.3978</td></tr>\n",
"\t<tr><th scope=row>Musi.no</th><td>0.0671</td><td> 0.7174</td><td> 0.3573</td><td>-0.0846</td><td>0.1148</td><td>0.0368</td><td>0.0023</td><td>0.3464</td><td>0.0859</td><td>0.0048</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 31 × 10\n",
"\\begin{tabular}{r|llllllllll}\n",
" & peso & Comp1 & Comp2 & Comp3 & Axis1 & Axis2 & Axis3 & Axis1 & Axis2 & Axis3\\\\\n",
" & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
"\\hline\n",
"\tTeat.sema & 0.0049 & -0.4980 & -0.0758 & -0.3073 & 0.0040 & 0.0001 & 0.0022 & 0.0075 & 0.0002 & 0.0029\\\\\n",
"\tTeat.mens & 0.0071 & -0.9211 & 0.5228 & 0.2842 & 0.0200 & 0.0084 & 0.0027 & 0.0378 & 0.0122 & 0.0036\\\\\n",
"\tTeat.trim & 0.0110 & -0.8722 & -0.5595 & -0.2800 & 0.0278 & 0.0148 & 0.0041 & 0.0537 & 0.0221 & 0.0055\\\\\n",
"\tTeat.seme & 0.0090 & -0.9047 & -0.3679 & -0.5120 & 0.0246 & 0.0053 & 0.0114 & 0.0470 & 0.0078 & 0.0150\\\\\n",
"\tTeat.anua & 0.0137 & -0.9318 & 0.1107 & 0.0765 & 0.0396 & 0.0007 & 0.0004 & 0.0778 & 0.0011 & 0.0005\\\\\n",
"\tTeat.no & 0.1209 & 0.3269 & 0.0382 & 0.0509 & 0.0430 & 0.0008 & 0.0015 & 0.2824 & 0.0039 & 0.0068\\\\\n",
"\tLibr.diar & 0.0274 & -0.8469 & 0.7776 & -0.1125 & 0.0654 & 0.0713 & 0.0017 & 0.1411 & 0.1190 & 0.0025\\\\\n",
"\tLibr.vdse & 0.0509 & -0.0674 & -0.4345 & 0.3652 & 0.0008 & 0.0414 & 0.0325 & 0.0020 & 0.0830 & 0.0587\\\\\n",
"\tLibr.sema & 0.0257 & 0.0215 & -0.4822 & -0.3068 & 0.0000 & 0.0257 & 0.0116 & 0.0001 & 0.0424 & 0.0172\\\\\n",
"\tLibr.mens & 0.0109 & -0.5762 & -0.2536 & -0.6726 & 0.0120 & 0.0030 & 0.0236 & 0.0233 & 0.0045 & 0.0317\\\\\n",
"\tLibr.trim & 0.0069 & 0.4624 & 0.0360 & -0.1619 & 0.0049 & 0.0000 & 0.0009 & 0.0093 & 0.0001 & 0.0011\\\\\n",
"\tLibr.anua & 0.0047 & -0.0670 & -0.8887 & -0.1619 & 0.0001 & 0.0158 & 0.0006 & 0.0001 & 0.0227 & 0.0008\\\\\n",
"\tLibr.no & 0.0402 & 0.7338 & 0.4944 & 0.0396 & 0.0719 & 0.0423 & 0.0003 & 0.1710 & 0.0776 & 0.0005\\\\\n",
"\tCine.mens & 0.0147 & -0.9917 & -0.0014 & 0.8793 & 0.0481 & 0.0000 & 0.0545 & 0.0952 & 0.0000 & 0.0749\\\\\n",
"\tCine.trim & 0.0175 & -0.7231 & 0.1767 & -0.3836 & 0.0304 & 0.0024 & 0.0123 & 0.0614 & 0.0037 & 0.0173\\\\\n",
"\tCine.seme & 0.0123 & -0.3904 & -0.5121 & -0.3316 & 0.0062 & 0.0138 & 0.0065 & 0.0121 & 0.0208 & 0.0087\\\\\n",
"\tCine.anua & 0.0139 & -0.2499 & 0.1000 & -0.1008 & 0.0029 & 0.0006 & 0.0007 & 0.0057 & 0.0009 & 0.0009\\\\\n",
"\tCine.no & 0.1083 & 0.3277 & 0.0168 & -0.0070 & 0.0387 & 0.0001 & 0.0000 & 0.1994 & 0.0005 & 0.0001\\\\\n",
"\tVide.diar & 0.0192 & -1.0668 & 1.2352 & 0.3794 & 0.0727 & 0.1261 & 0.0132 & 0.1481 & 0.1986 & 0.0187\\\\\n",
"\tVide.vdse & 0.0605 & -0.2837 & -0.5046 & 0.5419 & 0.0162 & 0.0663 & 0.0850 & 0.0458 & 0.1449 & 0.1672\\\\\n",
"\tVide.sema & 0.0342 & -0.1487 & -0.3900 & -0.8224 & 0.0025 & 0.0224 & 0.1106 & 0.0057 & 0.0392 & 0.1744\\\\\n",
"\tVide.mens & 0.0083 & -0.0903 & 0.0105 & -1.4645 & 0.0002 & 0.0000 & 0.0851 & 0.0004 & 0.0000 & 0.1122\\\\\n",
"\tVide.no & 0.0446 & 0.9752 & 0.4495 & 0.0041 & 0.1409 & 0.0388 & 0.0000 & 0.3471 & 0.0738 & 0.0000\\\\\n",
"\tRadi.diar & 0.0329 & -0.7241 & 0.7093 & -0.1031 & 0.0574 & 0.0712 & 0.0017 & 0.1289 & 0.1237 & 0.0026\\\\\n",
"\tRadi.vdse & 0.0333 & -0.0867 & -0.7197 & 0.4753 & 0.0008 & 0.0743 & 0.0360 & 0.0019 & 0.1294 & 0.0564\\\\\n",
"\tRadi.sema & 0.0084 & -0.3519 & -0.6191 & -1.8668 & 0.0034 & 0.0138 & 0.1396 & 0.0065 & 0.0203 & 0.1843\\\\\n",
"\tRadi.no & 0.0921 & 0.3220 & 0.0633 & 0.0346 & 0.0318 & 0.0016 & 0.0005 & 0.1280 & 0.0049 & 0.0015\\\\\n",
"\tMusi.diar & 0.0270 & -1.0375 & 1.0668 & 0.2862 & 0.0966 & 0.1322 & 0.0106 & 0.2079 & 0.2198 & 0.0158\\\\\n",
"\tMusi.vdse & 0.0594 & -0.2193 & -0.7871 & 0.4429 & 0.0095 & 0.1585 & 0.0558 & 0.0267 & 0.3435 & 0.1088\\\\\n",
"\tMusi.sema & 0.0132 & -0.5368 & -0.4506 & -2.1512 & 0.0126 & 0.0115 & 0.2922 & 0.0248 & 0.0175 & 0.3978\\\\\n",
"\tMusi.no & 0.0671 & 0.7174 & 0.3573 & -0.0846 & 0.1148 & 0.0368 & 0.0023 & 0.3464 & 0.0859 & 0.0048\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 31 × 10\n",
"\n",
"| <!--/--> | peso <dbl> | Comp1 <dbl> | Comp2 <dbl> | Comp3 <dbl> | Axis1 <dbl> | Axis2 <dbl> | Axis3 <dbl> | Axis1 <dbl> | Axis2 <dbl> | Axis3 <dbl> |\n",
"|---|---|---|---|---|---|---|---|---|---|---|\n",
"| Teat.sema | 0.0049 | -0.4980 | -0.0758 | -0.3073 | 0.0040 | 0.0001 | 0.0022 | 0.0075 | 0.0002 | 0.0029 |\n",
"| Teat.mens | 0.0071 | -0.9211 | 0.5228 | 0.2842 | 0.0200 | 0.0084 | 0.0027 | 0.0378 | 0.0122 | 0.0036 |\n",
"| Teat.trim | 0.0110 | -0.8722 | -0.5595 | -0.2800 | 0.0278 | 0.0148 | 0.0041 | 0.0537 | 0.0221 | 0.0055 |\n",
"| Teat.seme | 0.0090 | -0.9047 | -0.3679 | -0.5120 | 0.0246 | 0.0053 | 0.0114 | 0.0470 | 0.0078 | 0.0150 |\n",
"| Teat.anua | 0.0137 | -0.9318 | 0.1107 | 0.0765 | 0.0396 | 0.0007 | 0.0004 | 0.0778 | 0.0011 | 0.0005 |\n",
"| Teat.no | 0.1209 | 0.3269 | 0.0382 | 0.0509 | 0.0430 | 0.0008 | 0.0015 | 0.2824 | 0.0039 | 0.0068 |\n",
"| Libr.diar | 0.0274 | -0.8469 | 0.7776 | -0.1125 | 0.0654 | 0.0713 | 0.0017 | 0.1411 | 0.1190 | 0.0025 |\n",
"| Libr.vdse | 0.0509 | -0.0674 | -0.4345 | 0.3652 | 0.0008 | 0.0414 | 0.0325 | 0.0020 | 0.0830 | 0.0587 |\n",
"| Libr.sema | 0.0257 | 0.0215 | -0.4822 | -0.3068 | 0.0000 | 0.0257 | 0.0116 | 0.0001 | 0.0424 | 0.0172 |\n",
"| Libr.mens | 0.0109 | -0.5762 | -0.2536 | -0.6726 | 0.0120 | 0.0030 | 0.0236 | 0.0233 | 0.0045 | 0.0317 |\n",
"| Libr.trim | 0.0069 | 0.4624 | 0.0360 | -0.1619 | 0.0049 | 0.0000 | 0.0009 | 0.0093 | 0.0001 | 0.0011 |\n",
"| Libr.anua | 0.0047 | -0.0670 | -0.8887 | -0.1619 | 0.0001 | 0.0158 | 0.0006 | 0.0001 | 0.0227 | 0.0008 |\n",
"| Libr.no | 0.0402 | 0.7338 | 0.4944 | 0.0396 | 0.0719 | 0.0423 | 0.0003 | 0.1710 | 0.0776 | 0.0005 |\n",
"| Cine.mens | 0.0147 | -0.9917 | -0.0014 | 0.8793 | 0.0481 | 0.0000 | 0.0545 | 0.0952 | 0.0000 | 0.0749 |\n",
"| Cine.trim | 0.0175 | -0.7231 | 0.1767 | -0.3836 | 0.0304 | 0.0024 | 0.0123 | 0.0614 | 0.0037 | 0.0173 |\n",
"| Cine.seme | 0.0123 | -0.3904 | -0.5121 | -0.3316 | 0.0062 | 0.0138 | 0.0065 | 0.0121 | 0.0208 | 0.0087 |\n",
"| Cine.anua | 0.0139 | -0.2499 | 0.1000 | -0.1008 | 0.0029 | 0.0006 | 0.0007 | 0.0057 | 0.0009 | 0.0009 |\n",
"| Cine.no | 0.1083 | 0.3277 | 0.0168 | -0.0070 | 0.0387 | 0.0001 | 0.0000 | 0.1994 | 0.0005 | 0.0001 |\n",
"| Vide.diar | 0.0192 | -1.0668 | 1.2352 | 0.3794 | 0.0727 | 0.1261 | 0.0132 | 0.1481 | 0.1986 | 0.0187 |\n",
"| Vide.vdse | 0.0605 | -0.2837 | -0.5046 | 0.5419 | 0.0162 | 0.0663 | 0.0850 | 0.0458 | 0.1449 | 0.1672 |\n",
"| Vide.sema | 0.0342 | -0.1487 | -0.3900 | -0.8224 | 0.0025 | 0.0224 | 0.1106 | 0.0057 | 0.0392 | 0.1744 |\n",
"| Vide.mens | 0.0083 | -0.0903 | 0.0105 | -1.4645 | 0.0002 | 0.0000 | 0.0851 | 0.0004 | 0.0000 | 0.1122 |\n",
"| Vide.no | 0.0446 | 0.9752 | 0.4495 | 0.0041 | 0.1409 | 0.0388 | 0.0000 | 0.3471 | 0.0738 | 0.0000 |\n",
"| Radi.diar | 0.0329 | -0.7241 | 0.7093 | -0.1031 | 0.0574 | 0.0712 | 0.0017 | 0.1289 | 0.1237 | 0.0026 |\n",
"| Radi.vdse | 0.0333 | -0.0867 | -0.7197 | 0.4753 | 0.0008 | 0.0743 | 0.0360 | 0.0019 | 0.1294 | 0.0564 |\n",
"| Radi.sema | 0.0084 | -0.3519 | -0.6191 | -1.8668 | 0.0034 | 0.0138 | 0.1396 | 0.0065 | 0.0203 | 0.1843 |\n",
"| Radi.no | 0.0921 | 0.3220 | 0.0633 | 0.0346 | 0.0318 | 0.0016 | 0.0005 | 0.1280 | 0.0049 | 0.0015 |\n",
"| Musi.diar | 0.0270 | -1.0375 | 1.0668 | 0.2862 | 0.0966 | 0.1322 | 0.0106 | 0.2079 | 0.2198 | 0.0158 |\n",
"| Musi.vdse | 0.0594 | -0.2193 | -0.7871 | 0.4429 | 0.0095 | 0.1585 | 0.0558 | 0.0267 | 0.3435 | 0.1088 |\n",
"| Musi.sema | 0.0132 | -0.5368 | -0.4506 | -2.1512 | 0.0126 | 0.0115 | 0.2922 | 0.0248 | 0.0175 | 0.3978 |\n",
"| Musi.no | 0.0671 | 0.7174 | 0.3573 | -0.0846 | 0.1148 | 0.0368 | 0.0023 | 0.3464 | 0.0859 | 0.0048 |\n",
"\n"
],
"text/plain": [
" peso Comp1 Comp2 Comp3 Axis1 Axis2 Axis3 Axis1 Axis2 \n",
"Teat.sema 0.0049 -0.4980 -0.0758 -0.3073 0.0040 0.0001 0.0022 0.0075 0.0002\n",
"Teat.mens 0.0071 -0.9211 0.5228 0.2842 0.0200 0.0084 0.0027 0.0378 0.0122\n",
"Teat.trim 0.0110 -0.8722 -0.5595 -0.2800 0.0278 0.0148 0.0041 0.0537 0.0221\n",
"Teat.seme 0.0090 -0.9047 -0.3679 -0.5120 0.0246 0.0053 0.0114 0.0470 0.0078\n",
"Teat.anua 0.0137 -0.9318 0.1107 0.0765 0.0396 0.0007 0.0004 0.0778 0.0011\n",
"Teat.no 0.1209 0.3269 0.0382 0.0509 0.0430 0.0008 0.0015 0.2824 0.0039\n",
"Libr.diar 0.0274 -0.8469 0.7776 -0.1125 0.0654 0.0713 0.0017 0.1411 0.1190\n",
"Libr.vdse 0.0509 -0.0674 -0.4345 0.3652 0.0008 0.0414 0.0325 0.0020 0.0830\n",
"Libr.sema 0.0257 0.0215 -0.4822 -0.3068 0.0000 0.0257 0.0116 0.0001 0.0424\n",
"Libr.mens 0.0109 -0.5762 -0.2536 -0.6726 0.0120 0.0030 0.0236 0.0233 0.0045\n",
"Libr.trim 0.0069 0.4624 0.0360 -0.1619 0.0049 0.0000 0.0009 0.0093 0.0001\n",
"Libr.anua 0.0047 -0.0670 -0.8887 -0.1619 0.0001 0.0158 0.0006 0.0001 0.0227\n",
"Libr.no 0.0402 0.7338 0.4944 0.0396 0.0719 0.0423 0.0003 0.1710 0.0776\n",
"Cine.mens 0.0147 -0.9917 -0.0014 0.8793 0.0481 0.0000 0.0545 0.0952 0.0000\n",
"Cine.trim 0.0175 -0.7231 0.1767 -0.3836 0.0304 0.0024 0.0123 0.0614 0.0037\n",
"Cine.seme 0.0123 -0.3904 -0.5121 -0.3316 0.0062 0.0138 0.0065 0.0121 0.0208\n",
"Cine.anua 0.0139 -0.2499 0.1000 -0.1008 0.0029 0.0006 0.0007 0.0057 0.0009\n",
"Cine.no 0.1083 0.3277 0.0168 -0.0070 0.0387 0.0001 0.0000 0.1994 0.0005\n",
"Vide.diar 0.0192 -1.0668 1.2352 0.3794 0.0727 0.1261 0.0132 0.1481 0.1986\n",
"Vide.vdse 0.0605 -0.2837 -0.5046 0.5419 0.0162 0.0663 0.0850 0.0458 0.1449\n",
"Vide.sema 0.0342 -0.1487 -0.3900 -0.8224 0.0025 0.0224 0.1106 0.0057 0.0392\n",
"Vide.mens 0.0083 -0.0903 0.0105 -1.4645 0.0002 0.0000 0.0851 0.0004 0.0000\n",
"Vide.no 0.0446 0.9752 0.4495 0.0041 0.1409 0.0388 0.0000 0.3471 0.0738\n",
"Radi.diar 0.0329 -0.7241 0.7093 -0.1031 0.0574 0.0712 0.0017 0.1289 0.1237\n",
"Radi.vdse 0.0333 -0.0867 -0.7197 0.4753 0.0008 0.0743 0.0360 0.0019 0.1294\n",
"Radi.sema 0.0084 -0.3519 -0.6191 -1.8668 0.0034 0.0138 0.1396 0.0065 0.0203\n",
"Radi.no 0.0921 0.3220 0.0633 0.0346 0.0318 0.0016 0.0005 0.1280 0.0049\n",
"Musi.diar 0.0270 -1.0375 1.0668 0.2862 0.0966 0.1322 0.0106 0.2079 0.2198\n",
"Musi.vdse 0.0594 -0.2193 -0.7871 0.4429 0.0095 0.1585 0.0558 0.0267 0.3435\n",
"Musi.sema 0.0132 -0.5368 -0.4506 -2.1512 0.0126 0.0115 0.2922 0.0248 0.0175\n",
"Musi.no 0.0671 0.7174 0.3573 -0.0846 0.1148 0.0368 0.0023 0.3464 0.0859\n",
" Axis3 \n",
"Teat.sema 0.0029\n",
"Teat.mens 0.0036\n",
"Teat.trim 0.0055\n",
"Teat.seme 0.0150\n",
"Teat.anua 0.0005\n",
"Teat.no 0.0068\n",
"Libr.diar 0.0025\n",
"Libr.vdse 0.0587\n",
"Libr.sema 0.0172\n",
"Libr.mens 0.0317\n",
"Libr.trim 0.0011\n",
"Libr.anua 0.0008\n",
"Libr.no 0.0005\n",
"Cine.mens 0.0749\n",
"Cine.trim 0.0173\n",
"Cine.seme 0.0087\n",
"Cine.anua 0.0009\n",
"Cine.no 0.0001\n",
"Vide.diar 0.0187\n",
"Vide.vdse 0.1672\n",
"Vide.sema 0.1744\n",
"Vide.mens 0.1122\n",
"Vide.no 0.0000\n",
"Radi.diar 0.0026\n",
"Radi.vdse 0.0564\n",
"Radi.sema 0.1843\n",
"Radi.no 0.0015\n",
"Musi.diar 0.0158\n",
"Musi.vdse 0.1088\n",
"Musi.sema 0.3978\n",
"Musi.no 0.0048"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ayu<-inertia.dudi(acm,,T) \n",
"cat(\"\\ncategoría | peso | coordenadas | cont.absoluta | coseno cuadrado\")\n",
"round(cbind(peso=acm$cw,acm$co,ayu$col.abs/100,abs(ayu$col.rel)/100),4)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Variables suplementarias\n",
"\n",
"En la figura se muestran las categorías de las variables sociodemográficas, proyectadas como suplementarias en el primer plano factorial y las coordenadas y ayudas para la interpretación sobre los tres primeros ejes factoriales. \n",
"El plano debe verse como un *zoom* del centro de la figura. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Proyección de categorías suplementarias sobre el primer plano factorial del ACM de consumo cultural "
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"data": {
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+HyhxW82+ZXsidO8OSQ1TRPR0/UQRfiL4+0fNzq+5RbtCnd63NH2Dfp/6OnraZ3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\nRUXJz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QosZ/TIC0escqqV66lrtaa3f9KV+t/Ey27d8qRfMVkyZVmslN1Vq4t7sW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\nn9d/WOLxAAAAAElFTkSuQmCC",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"sc<-supqual(acm,Ys)\n",
"plotfp(as.data.frame(sc$coor),col=\"darkgreen\",cframe=1,gg=TRUE)\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Las categorías que tienen valores test inferiores a -2 y superiores a 2, son las que se pueden interpretar. Solo es pertinente interpretar el primer eje (horizontal) del plano factorial. \n",
"\n",
"Entonces, las diferencias del consumo cultural se pueden explicar en parte por el nivel socioeconómico (el estrato es una aproximación): el consumo cultural aumenta a medida que mejora el nivel socioeconómico. \n",
"Pero también por el parentesco con el jefe del hogar: los niños que viven con personas diferentes a los padres o abuelos tienen menor consumo cultural, y por la región geográfica donde viven: los niños de las regiones Atlántica, Bogotá y Central suelen tener mayor consumo cultural que los de las regiones Orinoquía-Amazonía y Oriental.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Coordenadas y ayudas para la interpretación de las categorías suplementarias del ACM de consumo cultural"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table class=\"dataframe\">\n",
"<caption>A data.frame: 18 × 11</caption>\n",
"<thead>\n",
"\t<tr><th></th><th scope=col>por</th><th scope=col>dis2</th><th scope=col>coor.Axis1</th><th scope=col>coor.Axis2</th><th scope=col>coor.Axis3</th><th scope=col>vt.Axis1</th><th scope=col>vt.Axis2</th><th scope=col>vt.Axis3</th><th scope=col>cos2.Axis1</th><th scope=col>cos2.Axis2</th><th scope=col>cos2.Axis3</th></tr>\n",
"\t<tr><th></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th><th scope=col><dbl></th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><th scope=row>Pare.hijo</th><td>42.4338</td><td> 0.3363</td><td>-0.0234</td><td>-0.0077</td><td> 0.0313</td><td>-1.7942</td><td>-0.5884</td><td> 2.3943</td><td>0.0016</td><td>0.0002</td><td>0.0029</td></tr>\n",
"\t<tr><th scope=row>Pare.niet</th><td>10.7020</td><td> 4.2984</td><td> 0.0100</td><td> 0.0435</td><td>-0.0882</td><td> 0.2151</td><td> 0.9309</td><td>-1.8874</td><td>0.0000</td><td>0.0004</td><td>0.0018</td></tr>\n",
"\t<tr><th scope=row>Pare.otro</th><td> 3.5673</td><td>14.8952</td><td> 0.2487</td><td>-0.0390</td><td>-0.1076</td><td> 2.8600</td><td>-0.4487</td><td>-1.2376</td><td>0.0042</td><td>0.0001</td><td>0.0008</td></tr>\n",
"\t<tr><th scope=row>Sexo.masc</th><td>28.4522</td><td> 0.9929</td><td> 0.0220</td><td> 0.0210</td><td> 0.0190</td><td> 0.9791</td><td> 0.9374</td><td> 0.8459</td><td>0.0005</td><td>0.0004</td><td>0.0004</td></tr>\n",
"\t<tr><th scope=row>Sexo.feme</th><td>28.2509</td><td> 1.0071</td><td>-0.0221</td><td>-0.0212</td><td>-0.0191</td><td>-0.9791</td><td>-0.9374</td><td>-0.8459</td><td>0.0005</td><td>0.0004</td><td>0.0004</td></tr>\n",
"\t<tr><th scope=row>Edad.a8</th><td>13.4350</td><td> 3.2206</td><td> 0.0568</td><td> 0.0087</td><td>-0.0218</td><td> 1.4060</td><td> 0.2148</td><td>-0.5387</td><td>0.0010</td><td>0.0000</td><td>0.0001</td></tr>\n",
"\t<tr><th scope=row>Edad.a9</th><td>13.6364</td><td> 3.1582</td><td> 0.0296</td><td> 0.0580</td><td>-0.0253</td><td> 0.7392</td><td> 1.4496</td><td>-0.6320</td><td>0.0003</td><td>0.0011</td><td>0.0002</td></tr>\n",
"\t<tr><th scope=row>Edad.a10</th><td>14.6720</td><td> 2.8647</td><td>-0.0187</td><td>-0.0200</td><td> 0.0473</td><td>-0.4908</td><td>-0.5243</td><td> 1.2406</td><td>0.0001</td><td>0.0001</td><td>0.0008</td></tr>\n",
"\t<tr><th scope=row>Edad.a11</th><td>14.9597</td><td> 2.7904</td><td>-0.0597</td><td>-0.0411</td><td>-0.0038</td><td>-1.5857</td><td>-1.0920</td><td>-0.1003</td><td>0.0013</td><td>0.0006</td><td>0.0000</td></tr>\n",
"\t<tr><th scope=row>Regi.Atla</th><td> 7.7100</td><td> 6.3545</td><td>-0.3159</td><td>-0.0028</td><td>-0.1254</td><td>-5.5613</td><td>-0.0501</td><td>-2.2086</td><td>0.0157</td><td>0.0000</td><td>0.0025</td></tr>\n",
"\t<tr><th scope=row>Regi.Orie</th><td>12.9459</td><td> 3.3800</td><td> 0.2222</td><td> 0.0664</td><td> 0.0920</td><td> 5.3655</td><td> 1.6021</td><td> 2.2202</td><td>0.0146</td><td>0.0013</td><td>0.0025</td></tr>\n",
"\t<tr><th scope=row>Regi.Cent</th><td> 9.4361</td><td> 5.0091</td><td>-0.1417</td><td>-0.0137</td><td>-0.0695</td><td>-2.8108</td><td>-0.2708</td><td>-1.3781</td><td>0.0040</td><td>0.0000</td><td>0.0010</td></tr>\n",
"\t<tr><th scope=row>Regi.Paci</th><td> 8.8032</td><td> 5.4412</td><td> 0.0331</td><td> 0.0532</td><td> 0.0879</td><td> 0.6302</td><td> 1.0116</td><td> 1.6719</td><td>0.0002</td><td>0.0005</td><td>0.0014</td></tr>\n",
"\t<tr><th scope=row>Regi.Bogo</th><td> 8.9183</td><td> 5.3581</td><td>-0.2375</td><td>-0.0971</td><td> 0.0062</td><td>-4.5544</td><td>-1.8610</td><td> 0.1185</td><td>0.0105</td><td>0.0018</td><td>0.0000</td></tr>\n",
"\t<tr><th scope=row>Regi.OrAm</th><td> 8.8895</td><td> 5.3786</td><td> 0.3062</td><td>-0.0350</td><td>-0.0446</td><td> 5.8606</td><td>-0.6691</td><td>-0.8533</td><td>0.0174</td><td>0.0002</td><td>0.0004</td></tr>\n",
"\t<tr><th scope=row>Estr.0o1</th><td>23.8493</td><td> 1.3776</td><td> 0.2861</td><td> 0.0183</td><td> 0.0100</td><td>10.8189</td><td> 0.6922</td><td> 0.3784</td><td>0.0594</td><td>0.0002</td><td>0.0001</td></tr>\n",
"\t<tr><th scope=row>Estr.2</th><td>21.9793</td><td> 1.5798</td><td>-0.1014</td><td>-0.0083</td><td>-0.0428</td><td>-3.5816</td><td>-0.2928</td><td>-1.5131</td><td>0.0065</td><td>0.0000</td><td>0.0012</td></tr>\n",
"\t<tr><th scope=row>Estr.3oM</th><td>10.8746</td><td> 4.2143</td><td>-0.4224</td><td>-0.0234</td><td> 0.0647</td><td>-9.1334</td><td>-0.5056</td><td> 1.3980</td><td>0.0423</td><td>0.0001</td><td>0.0010</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 18 × 11\n",
"\\begin{tabular}{r|lllllllllll}\n",
" & por & dis2 & coor.Axis1 & coor.Axis2 & coor.Axis3 & vt.Axis1 & vt.Axis2 & vt.Axis3 & cos2.Axis1 & cos2.Axis2 & cos2.Axis3\\\\\n",
" & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
"\\hline\n",
"\tPare.hijo & 42.4338 & 0.3363 & -0.0234 & -0.0077 & 0.0313 & -1.7942 & -0.5884 & 2.3943 & 0.0016 & 0.0002 & 0.0029\\\\\n",
"\tPare.niet & 10.7020 & 4.2984 & 0.0100 & 0.0435 & -0.0882 & 0.2151 & 0.9309 & -1.8874 & 0.0000 & 0.0004 & 0.0018\\\\\n",
"\tPare.otro & 3.5673 & 14.8952 & 0.2487 & -0.0390 & -0.1076 & 2.8600 & -0.4487 & -1.2376 & 0.0042 & 0.0001 & 0.0008\\\\\n",
"\tSexo.masc & 28.4522 & 0.9929 & 0.0220 & 0.0210 & 0.0190 & 0.9791 & 0.9374 & 0.8459 & 0.0005 & 0.0004 & 0.0004\\\\\n",
"\tSexo.feme & 28.2509 & 1.0071 & -0.0221 & -0.0212 & -0.0191 & -0.9791 & -0.9374 & -0.8459 & 0.0005 & 0.0004 & 0.0004\\\\\n",
"\tEdad.a8 & 13.4350 & 3.2206 & 0.0568 & 0.0087 & -0.0218 & 1.4060 & 0.2148 & -0.5387 & 0.0010 & 0.0000 & 0.0001\\\\\n",
"\tEdad.a9 & 13.6364 & 3.1582 & 0.0296 & 0.0580 & -0.0253 & 0.7392 & 1.4496 & -0.6320 & 0.0003 & 0.0011 & 0.0002\\\\\n",
"\tEdad.a10 & 14.6720 & 2.8647 & -0.0187 & -0.0200 & 0.0473 & -0.4908 & -0.5243 & 1.2406 & 0.0001 & 0.0001 & 0.0008\\\\\n",
"\tEdad.a11 & 14.9597 & 2.7904 & -0.0597 & -0.0411 & -0.0038 & -1.5857 & -1.0920 & -0.1003 & 0.0013 & 0.0006 & 0.0000\\\\\n",
"\tRegi.Atla & 7.7100 & 6.3545 & -0.3159 & -0.0028 & -0.1254 & -5.5613 & -0.0501 & -2.2086 & 0.0157 & 0.0000 & 0.0025\\\\\n",
"\tRegi.Orie & 12.9459 & 3.3800 & 0.2222 & 0.0664 & 0.0920 & 5.3655 & 1.6021 & 2.2202 & 0.0146 & 0.0013 & 0.0025\\\\\n",
"\tRegi.Cent & 9.4361 & 5.0091 & -0.1417 & -0.0137 & -0.0695 & -2.8108 & -0.2708 & -1.3781 & 0.0040 & 0.0000 & 0.0010\\\\\n",
"\tRegi.Paci & 8.8032 & 5.4412 & 0.0331 & 0.0532 & 0.0879 & 0.6302 & 1.0116 & 1.6719 & 0.0002 & 0.0005 & 0.0014\\\\\n",
"\tRegi.Bogo & 8.9183 & 5.3581 & -0.2375 & -0.0971 & 0.0062 & -4.5544 & -1.8610 & 0.1185 & 0.0105 & 0.0018 & 0.0000\\\\\n",
"\tRegi.OrAm & 8.8895 & 5.3786 & 0.3062 & -0.0350 & -0.0446 & 5.8606 & -0.6691 & -0.8533 & 0.0174 & 0.0002 & 0.0004\\\\\n",
"\tEstr.0o1 & 23.8493 & 1.3776 & 0.2861 & 0.0183 & 0.0100 & 10.8189 & 0.6922 & 0.3784 & 0.0594 & 0.0002 & 0.0001\\\\\n",
"\tEstr.2 & 21.9793 & 1.5798 & -0.1014 & -0.0083 & -0.0428 & -3.5816 & -0.2928 & -1.5131 & 0.0065 & 0.0000 & 0.0012\\\\\n",
"\tEstr.3oM & 10.8746 & 4.2143 & -0.4224 & -0.0234 & 0.0647 & -9.1334 & -0.5056 & 1.3980 & 0.0423 & 0.0001 & 0.0010\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 18 × 11\n",
"\n",
"| <!--/--> | por <dbl> | dis2 <dbl> | coor.Axis1 <dbl> | coor.Axis2 <dbl> | coor.Axis3 <dbl> | vt.Axis1 <dbl> | vt.Axis2 <dbl> | vt.Axis3 <dbl> | cos2.Axis1 <dbl> | cos2.Axis2 <dbl> | cos2.Axis3 <dbl> |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| Pare.hijo | 42.4338 | 0.3363 | -0.0234 | -0.0077 | 0.0313 | -1.7942 | -0.5884 | 2.3943 | 0.0016 | 0.0002 | 0.0029 |\n",
"| Pare.niet | 10.7020 | 4.2984 | 0.0100 | 0.0435 | -0.0882 | 0.2151 | 0.9309 | -1.8874 | 0.0000 | 0.0004 | 0.0018 |\n",
"| Pare.otro | 3.5673 | 14.8952 | 0.2487 | -0.0390 | -0.1076 | 2.8600 | -0.4487 | -1.2376 | 0.0042 | 0.0001 | 0.0008 |\n",
"| Sexo.masc | 28.4522 | 0.9929 | 0.0220 | 0.0210 | 0.0190 | 0.9791 | 0.9374 | 0.8459 | 0.0005 | 0.0004 | 0.0004 |\n",
"| Sexo.feme | 28.2509 | 1.0071 | -0.0221 | -0.0212 | -0.0191 | -0.9791 | -0.9374 | -0.8459 | 0.0005 | 0.0004 | 0.0004 |\n",
"| Edad.a8 | 13.4350 | 3.2206 | 0.0568 | 0.0087 | -0.0218 | 1.4060 | 0.2148 | -0.5387 | 0.0010 | 0.0000 | 0.0001 |\n",
"| Edad.a9 | 13.6364 | 3.1582 | 0.0296 | 0.0580 | -0.0253 | 0.7392 | 1.4496 | -0.6320 | 0.0003 | 0.0011 | 0.0002 |\n",
"| Edad.a10 | 14.6720 | 2.8647 | -0.0187 | -0.0200 | 0.0473 | -0.4908 | -0.5243 | 1.2406 | 0.0001 | 0.0001 | 0.0008 |\n",
"| Edad.a11 | 14.9597 | 2.7904 | -0.0597 | -0.0411 | -0.0038 | -1.5857 | -1.0920 | -0.1003 | 0.0013 | 0.0006 | 0.0000 |\n",
"| Regi.Atla | 7.7100 | 6.3545 | -0.3159 | -0.0028 | -0.1254 | -5.5613 | -0.0501 | -2.2086 | 0.0157 | 0.0000 | 0.0025 |\n",
"| Regi.Orie | 12.9459 | 3.3800 | 0.2222 | 0.0664 | 0.0920 | 5.3655 | 1.6021 | 2.2202 | 0.0146 | 0.0013 | 0.0025 |\n",
"| Regi.Cent | 9.4361 | 5.0091 | -0.1417 | -0.0137 | -0.0695 | -2.8108 | -0.2708 | -1.3781 | 0.0040 | 0.0000 | 0.0010 |\n",
"| Regi.Paci | 8.8032 | 5.4412 | 0.0331 | 0.0532 | 0.0879 | 0.6302 | 1.0116 | 1.6719 | 0.0002 | 0.0005 | 0.0014 |\n",
"| Regi.Bogo | 8.9183 | 5.3581 | -0.2375 | -0.0971 | 0.0062 | -4.5544 | -1.8610 | 0.1185 | 0.0105 | 0.0018 | 0.0000 |\n",
"| Regi.OrAm | 8.8895 | 5.3786 | 0.3062 | -0.0350 | -0.0446 | 5.8606 | -0.6691 | -0.8533 | 0.0174 | 0.0002 | 0.0004 |\n",
"| Estr.0o1 | 23.8493 | 1.3776 | 0.2861 | 0.0183 | 0.0100 | 10.8189 | 0.6922 | 0.3784 | 0.0594 | 0.0002 | 0.0001 |\n",
"| Estr.2 | 21.9793 | 1.5798 | -0.1014 | -0.0083 | -0.0428 | -3.5816 | -0.2928 | -1.5131 | 0.0065 | 0.0000 | 0.0012 |\n",
"| Estr.3oM | 10.8746 | 4.2143 | -0.4224 | -0.0234 | 0.0647 | -9.1334 | -0.5056 | 1.3980 | 0.0423 | 0.0001 | 0.0010 |\n",
"\n"
],
"text/plain": [
" por dis2 coor.Axis1 coor.Axis2 coor.Axis3 vt.Axis1 vt.Axis2\n",
"Pare.hijo 42.4338 0.3363 -0.0234 -0.0077 0.0313 -1.7942 -0.5884 \n",
"Pare.niet 10.7020 4.2984 0.0100 0.0435 -0.0882 0.2151 0.9309 \n",
"Pare.otro 3.5673 14.8952 0.2487 -0.0390 -0.1076 2.8600 -0.4487 \n",
"Sexo.masc 28.4522 0.9929 0.0220 0.0210 0.0190 0.9791 0.9374 \n",
"Sexo.feme 28.2509 1.0071 -0.0221 -0.0212 -0.0191 -0.9791 -0.9374 \n",
"Edad.a8 13.4350 3.2206 0.0568 0.0087 -0.0218 1.4060 0.2148 \n",
"Edad.a9 13.6364 3.1582 0.0296 0.0580 -0.0253 0.7392 1.4496 \n",
"Edad.a10 14.6720 2.8647 -0.0187 -0.0200 0.0473 -0.4908 -0.5243 \n",
"Edad.a11 14.9597 2.7904 -0.0597 -0.0411 -0.0038 -1.5857 -1.0920 \n",
"Regi.Atla 7.7100 6.3545 -0.3159 -0.0028 -0.1254 -5.5613 -0.0501 \n",
"Regi.Orie 12.9459 3.3800 0.2222 0.0664 0.0920 5.3655 1.6021 \n",
"Regi.Cent 9.4361 5.0091 -0.1417 -0.0137 -0.0695 -2.8108 -0.2708 \n",
"Regi.Paci 8.8032 5.4412 0.0331 0.0532 0.0879 0.6302 1.0116 \n",
"Regi.Bogo 8.9183 5.3581 -0.2375 -0.0971 0.0062 -4.5544 -1.8610 \n",
"Regi.OrAm 8.8895 5.3786 0.3062 -0.0350 -0.0446 5.8606 -0.6691 \n",
"Estr.0o1 23.8493 1.3776 0.2861 0.0183 0.0100 10.8189 0.6922 \n",
"Estr.2 21.9793 1.5798 -0.1014 -0.0083 -0.0428 -3.5816 -0.2928 \n",
"Estr.3oM 10.8746 4.2143 -0.4224 -0.0234 0.0647 -9.1334 -0.5056 \n",
" vt.Axis3 cos2.Axis1 cos2.Axis2 cos2.Axis3\n",
"Pare.hijo 2.3943 0.0016 0.0002 0.0029 \n",
"Pare.niet -1.8874 0.0000 0.0004 0.0018 \n",
"Pare.otro -1.2376 0.0042 0.0001 0.0008 \n",
"Sexo.masc 0.8459 0.0005 0.0004 0.0004 \n",
"Sexo.feme -0.8459 0.0005 0.0004 0.0004 \n",
"Edad.a8 -0.5387 0.0010 0.0000 0.0001 \n",
"Edad.a9 -0.6320 0.0003 0.0011 0.0002 \n",
"Edad.a10 1.2406 0.0001 0.0001 0.0008 \n",
"Edad.a11 -0.1003 0.0013 0.0006 0.0000 \n",
"Regi.Atla -2.2086 0.0157 0.0000 0.0025 \n",
"Regi.Orie 2.2202 0.0146 0.0013 0.0025 \n",
"Regi.Cent -1.3781 0.0040 0.0000 0.0010 \n",
"Regi.Paci 1.6719 0.0002 0.0005 0.0014 \n",
"Regi.Bogo 0.1185 0.0105 0.0018 0.0000 \n",
"Regi.OrAm -0.8533 0.0174 0.0002 0.0004 \n",
"Estr.0o1 0.3784 0.0594 0.0002 0.0001 \n",
"Estr.2 -1.5131 0.0065 0.0000 0.0012 \n",
"Estr.3oM 1.3980 0.0423 0.0001 0.0010 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"round(data.frame(por=sc$ncat/34.76,dis2=sc$dis2,coor=sc$coor,vt=sc$tv,cos2=sc$cos2),4)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Relación entre variables y ejes\n"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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JkNCBAgQIAAAQIECBDoqoABUld7dpF2bd68+dLKIm9ZRIAAAQIECBAgQIBABDzm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rkvqM0bR9Jme7GCBNR/vXrQf3beFQHsiy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\nAQIECBAgQIAAAQIECBAgMEMC/w/frkPTECUYHAAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"plotfp(acm$cr,xlim=c(0,0.6),cframe=1)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Conclusiones del análisis ACM de frecuencias de lectura de niños\n",
"\n",
"- Los niños entre 8 y 11 años de la muestra del Dane14 tienen un bajo consumo cultural: menos de la mitad asisten a teatro, cine o escuchan radio; casi la cuarta parte dice no leer libros. .\n",
"\n",
"- Las categorías se ordenan en el primer plano factorial, en forma de parábola, lo que muestra la tendencia general de que los niños que tienen bajo consumo cultural, lo tienen simultáneamente en las seis actividades. Entonces, el primer plano factorial es un indicador del consumo cultural y se pueden vislumbrar grupos de niños: los ubicados arriba a la izquierda son los de mayor consumo y los de arriba a la derecha los de menor consumo. En el centro del plano hacia abajo se ubican los de consumo medio.\n",
"\n",
"- Si se desea ordenar a los niños por su consumo cultural, se pueden utilizar las coordenadas del primer eje, pues este es también un indicador de consumo cultural.\n",
"\n",
"- El nivel de consumo cultural está explicado en parte, por el nivel socioeconómico (aproximado con el estrato), la relación con el jefe del hogar y la región donde viven los niños. Los niños suelen tener más consumo cultural a mayor nivel socioeconómica o si viven con padres o abuelos y si son de las regiones Atlántica, Bogotá o Central.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# FIN"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"[Volver al inicio](#Contenido)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"colab": {
"collapsed_sections": [],
"name": "ACM.ipynb",
"provenance": []
},
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
},
"language_info": {
"codemirror_mode": "r",
"file_extension": ".r",
"mimetype": "text/x-r-source",
"name": "R",
"pygments_lexer": "r",
"version": "4.1.2"
}
},
"nbformat": 4,
"nbformat_minor": 4
}