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Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham's package development philosophy. In the process, you'll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language.Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You'll learn to focus on what you want your package to do, rather than think about package structure. Ideal for developers, data scientists, and programmers with various backgrounds, this book starts with the basics and shows you how to improve your package writing over time. You'll learn to focus on what you want your package to do, rather than think about package structure

This example-based general introduction to the statistical computing environment does not assume any previous familiarity with R or other software packages. R functions are compellingly presented in the context of interesting applications with real data.

"Joint Species Distribution Modelling (JSDM) is a fastdeveloping field and promises to revolutionise how data on ecological communities are analysed and interpreted. Written for both readers with a limited statistical background, and those with statistical expertise, this book provides a comprehensive account of JSDM. It enables readers to integrate data on species abundances, environmental covariates, species traits, phylogenetic relationships, and the spatio-temporal context in which the data have been acquired. Step-by-step coverage of the full technical detail of statistical methods is provided, as well as advice on interpreting results of statistical analyses in the broader context of modern community ecology theory. With the advantage of numerous example R-scripts, this is an ideal guide to help graduate students and researchers learn how to conduct and interpret statistical analyses in practice with the R package HMSC-R, providing a fast starting point for applying joint species distribution modelling to their own data"--

The Preliminaries. Why R? -- The R Basics -- Data Preparation and Other Tricks -- Exploratory Data Analysis -- Probability and Inference. Probability Theory -- Probability and Sampling Distributions -- Parametric Inference -- Nonparametric Inference -- Bayesian Inference -- Stochastic Processes and Monte Carlo. Stochastic Processes -- Monte Carlo Computations -- Linear Models. Linear Regression Models -- Experimental Designs -- Multivariate Statistical Analysis - I -- Multivariate Statistical Analysis - II -- Categorical Data Analysis -- Generalized Linear Models -- Appendix A: Open Source Software: An Epilogue -- Appendix B: The Statistical Tables