# Using this book

## 0.1 Why should you read this book?

The goal of this bookdown is to provide a complete overview of the theory and methodology of two topics (at this point) within spatial capture-recapture:

1. Integrating telemtry data to estimate resource selection functions.
2. Optimizing sampling design toward statistical objectives

More broadly, by providing them with a thorough discussion of these advanced topics, we aim to empower our users to apply these tools in their own research.

## 0.2 Why should you use oSCR

The main function in oSCR performs likelihood analysis of several classes of spatial capture-recapture (SCR) models. There are also a suite of helper functions for formatting and processing data objects. Here are a few of the things that motivated our development of the package:

1. 100% native R code, making it (reasonably) accessible to people who know R and presumably extensible by ordinary R programmers.
2. Because it’s written in R, you can look at the code to figure out exactly what’s going on.
3. It’s a bit slower compared to secr, but we think it’s quite robust to massive-sized problems.
4. The data structure is relatively simple, just as ordinary R lists (for the most part).
5. The models accommodate least-cost path models and models that include telemetry data and resource selection functions.
6. oSCR forces you to define the state-space of the point process which we think is important to understanding an analysis.

## 0.3 Getting set up

So, using this book of course requires that the oSCR package is loaded:

#remotes::install_github("jaroyle/oSCR")
library(oSCR)

But you will also need a few others:

library(ggplot2)
library(raster)
library(sf)
library(viridis)

If you have any issues or questions, we have a very responsive, and friendly user group.