# oSCR vignettes

*2020-08-13*

# 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:

- Integrating telemtry data to estimate resource selection functions.
- 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:

- 100% native
`R`

code, making it (reasonably) accessible to people who know`R`

and presumably extensible by ordinary`R`

programmers. - Because it’s written in
`R`

, you can look at the code to figure out exactly what’s going on. - It’s a bit slower compared to
`secr`

, but we think it’s quite robust to massive-sized problems. - The data structure is relatively simple, just as ordinary
`R`

lists (for the most part). - The models accommodate least-cost path models and models that include telemetry data and resource selection functions.
`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:

But you will also need a few others:

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