---
title: "Plotting the predicted bycatch distribution"
author: ""
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Plotting the predicted bycatch distribution}
  %\VignetteEngine{knitr::rmarkdown}
  \usepackage[utf8]{inputenc}
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r, results = "hide", message = FALSE, warning = FALSE}
library(bycatch)
set.seed(123)
```

`plot_pred_distribution()` plots a histogram of the posterior distribution of predicted bycatch rate (lambda of the Poisson) for a single year, accounting for effort but not for observer coverage. For hurdle models, the distribution shown is the total predicted bycatch rate, combining the zero and non-zero components.

### Load data

```{r data}
# replace this with your own data frame
d <- data.frame(
  "Year" = 2002:2014,
  "Takes" = c(0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0, 0, 0),
  "expansionRate" = c(24, 22, 14, 32, 28, 25, 30, 7, 26, 21, 22, 23, 27),
  "Sets" = c(391, 340, 330, 660, 470, 500, 330, 287, 756, 673, 532, 351, 486)
)
```

### Fit a model

```{r fit, results = "hide", message = FALSE, warning = FALSE}
fit <- fit_bycatch(Takes ~ 1,
  data = d, time = "Year",
  effort = "Sets",
  family = "poisson",
  expansion_rate = "expansionRate",
  time_varying = FALSE
)
```

### Plot the prediction distribution for a single year

`year` selects which year (from the time column used in `fit_bycatch()`) to show the distribution for, and `breaks` controls the histogram bin width (it defaults to integer-width bins).

```{r plot, fig.width = 7, fig.height = 5}
plot_pred_distribution(fit,
  year = 2014,
  xlab = "Predicted Bycatch",
  ylab = "Frequency"
)
```