{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Time Series Regression - arima\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Loading required package: daltoolbox\n",
"\n",
"Registered S3 method overwritten by 'quantmod':\n",
" method from\n",
" as.zoo.data.frame zoo \n",
"\n",
"\n",
"Attaching package: ‘daltoolbox’\n",
"\n",
"\n",
"The following object is masked from ‘package:base’:\n",
"\n",
" transform\n",
"\n",
"\n"
]
}
],
"source": [
"# DAL ToolBox\n",
"# version 1.1.727\n",
"\n",
"source(\"https://raw.githubusercontent.com/cefet-rj-dal/daltoolbox/main/jupyter.R\")\n",
"\n",
"#loading DAL\n",
"load_library(\"daltoolbox\") "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Series for studying"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"A matrix: 3 × 1 of type dbl\n",
"\n",
"\tt0 |
\n",
"\n",
"\n",
"\t0.0000000 |
\n",
"\t0.2474040 |
\n",
"\t0.4794255 |
\n",
"\n",
"
\n"
],
"text/latex": [
"A matrix: 3 × 1 of type dbl\n",
"\\begin{tabular}{l}\n",
" t0\\\\\n",
"\\hline\n",
"\t 0.0000000\\\\\n",
"\t 0.2474040\\\\\n",
"\t 0.4794255\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A matrix: 3 × 1 of type dbl\n",
"\n",
"| t0 |\n",
"|---|\n",
"| 0.0000000 |\n",
"| 0.2474040 |\n",
"| 0.4794255 |\n",
"\n"
],
"text/plain": [
" t0 \n",
"[1,] 0.0000000\n",
"[2,] 0.2474040\n",
"[3,] 0.4794255"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"data(sin_data)\n",
"ts <- ts_data(sin_data$y, 0)\n",
"ts_head(ts, 3)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
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Fahjowb9zPPKkvnIi63aFBK/JnqLYEi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",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"library(ggplot2)\n",
"plot_ts(x=sin_data$x, y=sin_data$y) + theme(text = element_text(size=16))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### data sampling"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"samp <- ts_sample(ts, test_size = 5)\n",
"io_train <- ts_projection(samp$train)\n",
"io_test <- ts_projection(samp$test)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Model training"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"model <- ts_arima()\n",
"model <- fit(model, x=io_train$input, y=io_train$output)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Evaluation of adjustment"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"0.0285768645342128"
],
"text/latex": [
"0.0285768645342128"
],
"text/markdown": [
"0.0285768645342128"
],
"text/plain": [
"[1] 0.02857686"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"adjust <- predict(model, io_train$input)\n",
"adjust <- as.vector(adjust)\n",
"output <- as.vector(io_train$output)\n",
"ev_adjust <- evaluate(model, output, adjust)\n",
"ev_adjust$mse"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Prediction of test"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\t- $values
\n",
"\t\t- \n",
"
- 0.412118485241757
- 0.173889485380434
- -0.0751511204618093
- -0.319519193622274
- -0.54402111088937
\n",
" \n",
"\t- $prediction
\n",
"\t\t- \n",
"
- 0.601137422519967
- 0.578441403730991
- 0.556602275978195
- 0.535587687233026
- 0.515366506921828
\n",
" \n",
"\t- $smape
\n",
"\t\t- 1.48971098704162
\n",
"\t- $mse
\n",
"\t\t- 0.490402533932429
\n",
"\t- $R2
\n",
"\t\t- -3.23563201561947
\n",
"\t- $metrics
\n",
"\t\t\n",
"A data.frame: 1 × 3\n",
"\n",
"\tmse | smape | R2 |
\n",
"\t<dbl> | <dbl> | <dbl> |
\n",
"\n",
"\n",
"\t0.4904025 | 1.489711 | -3.235632 |
\n",
"\n",
"
\n",
" \n",
"
\n"
],
"text/latex": [
"\\begin{description}\n",
"\\item[\\$values] \\begin{enumerate*}\n",
"\\item 0.412118485241757\n",
"\\item 0.173889485380434\n",
"\\item -0.0751511204618093\n",
"\\item -0.319519193622274\n",
"\\item -0.54402111088937\n",
"\\end{enumerate*}\n",
"\n",
"\\item[\\$prediction] \\begin{enumerate*}\n",
"\\item 0.601137422519967\n",
"\\item 0.578441403730991\n",
"\\item 0.556602275978195\n",
"\\item 0.535587687233026\n",
"\\item 0.515366506921828\n",
"\\end{enumerate*}\n",
"\n",
"\\item[\\$smape] 1.48971098704162\n",
"\\item[\\$mse] 0.490402533932429\n",
"\\item[\\$R2] -3.23563201561947\n",
"\\item[\\$metrics] A data.frame: 1 × 3\n",
"\\begin{tabular}{lll}\n",
" mse & smape & R2\\\\\n",
" & & \\\\\n",
"\\hline\n",
"\t 0.4904025 & 1.489711 & -3.235632\\\\\n",
"\\end{tabular}\n",
"\n",
"\\end{description}\n"
],
"text/markdown": [
"$values\n",
": 1. 0.412118485241757\n",
"2. 0.173889485380434\n",
"3. -0.0751511204618093\n",
"4. -0.319519193622274\n",
"5. -0.54402111088937\n",
"\n",
"\n",
"\n",
"$prediction\n",
": 1. 0.601137422519967\n",
"2. 0.578441403730991\n",
"3. 0.556602275978195\n",
"4. 0.535587687233026\n",
"5. 0.515366506921828\n",
"\n",
"\n",
"\n",
"$smape\n",
": 1.48971098704162\n",
"$mse\n",
": 0.490402533932429\n",
"$R2\n",
": -3.23563201561947\n",
"$metrics\n",
": \n",
"A data.frame: 1 × 3\n",
"\n",
"| mse <dbl> | smape <dbl> | R2 <dbl> |\n",
"|---|---|---|\n",
"| 0.4904025 | 1.489711 | -3.235632 |\n",
"\n",
"\n",
"\n",
"\n"
],
"text/plain": [
"$values\n",
"[1] 0.41211849 0.17388949 -0.07515112 -0.31951919 -0.54402111\n",
"\n",
"$prediction\n",
"[1] 0.6011374 0.5784414 0.5566023 0.5355877 0.5153665\n",
"\n",
"$smape\n",
"[1] 1.489711\n",
"\n",
"$mse\n",
"[1] 0.4904025\n",
"\n",
"$R2\n",
"[1] -3.235632\n",
"\n",
"$metrics\n",
" mse smape R2\n",
"1 0.4904025 1.489711 -3.235632\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"prediction <- predict(model, x=io_test$input[1,], steps_ahead=5)\n",
"prediction <- as.vector(prediction)\n",
"output <- as.vector(io_test$output)\n",
"ev_test <- evaluate(model, output, prediction)\n",
"ev_test"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Plot results"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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AgWdqRi5eXl33//vaWlpaq2uN6/H2++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\nRK5CYII=",
"text/plain": [
"plot without title"
]
},
"metadata": {
"image/png": {
"height": 420,
"width": 420
}
},
"output_type": "display_data"
}
],
"source": [
"yvalues <- c(io_train$output, io_test$output)\n",
"plot_ts_pred(y=yvalues, yadj=adjust, ypre=prediction) + theme(text = element_text(size=16))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"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": "4.4.2"
}
},
"nbformat": 4,
"nbformat_minor": 4
}