---
title: "Small Rmarkdown example with opticut and knitr"
date: "`r format(Sys.time(), '%B %d, %Y')`"
output: pdf_document
---

# Introduction

This is a small example demonstrating how to include
opticut results into Rmarkdown (Rmd) documents.

```{r setup}
library(opticut)
library(knitr)
ocoptions(cut=-Inf)
```

# Analysis

## Data set

We have the following data set:

```{r data}
## community data
y <- cbind(
    Sp1=c(4,6,3,5, 5,6,3,4, 4,1,3,2),
    Sp2=c(0,0,0,0, 1,0,0,1, 4,2,3,4),
    Sp3=c(0,0,3,0, 2,3,0,5, 5,6,3,4))

## stratification
g <-    c(1,1,1,1, 2,2,2,2, 3,3,3,3)
```

## Finding optimal partitions

Here is the real deal:

```{r opticut}
oc <- opticut(formula = y ~ 1, strata = g, dist = "poisson")
summary(oc)
oc$species[[1]]
```

The opticut object and its summary are lists, thus the relevant
information need to be coerced into data frame using
the `as.data.frame` method:

```{r table-opticut}
kable(as.data.frame(oc))
```

Single species result is a data frame:

```{r table-opticut1}
kable(oc$species[[1]], digits=3)
```

## Plots

Visualizing the results:

```{r figure}
plot(oc)
```

## Quantifying uncertainty

```{r uncertainty}
uc <- uncertainty(oc, type = "asymp", B = 999)
summary(uc)
```

The opticut object and its summary are lists, thus the relevant
information need to be coerced into data frame using
the `as.data.frame` method:

```{r table-uncertainty}
kable(as.data.frame(uc))
```
