Advanced R

Advanced R
Authors
Wiley, Matt & Wiley, Joshua F.
Publisher
Apress
ISBN
9781484220764
Date
2017-03-10T00:00:00+00:00
Size
1.92 MB
Lang
en
Downloaded: 17 times

This in-depth advanced guide shows you how to conduct data analysis using the popular R language and how with some practical programming, you can make your work more efficient by writing functions or packages, and how to automate running code and the creation of reports to share your results.

This book is not designed to teach advanced R programming nor to teach the theory behind statistical procedures. Rather, this is designed to be a practical guide moving beyond merely using R to programming in R to automate tasks.

This book will also show how to do data manipulation in R including connecting R to data bases such as SQL and a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, and machine learning techniques.

The book closes with a hands-on section to get R running in the cloud. Each chapter also includes a detailed bibliography with references to research articles and other resources that cover relevant conceptual and theoretical topics.

What You'll Learn:

How to write and document R functions How to make an R package and share it via GitHub or privately How to add tests to R code to insure it works as intended How to add automatic package building with GitHub How to have R talk directly to data bases and do complex data management How to conduct advanced analyses in R including: generalized linear models, generalized additive models, and mixed effects models How to address missing data using multiple imputation in R How to run R in the Amazon cloud How to generate presentation-ready tables and reports using R

Audience: Advanced R: Applied Programming and Data Analysis is intended for working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to take their R coding and programming to the next level, automate repetitive tasks, and use R to speed up their workflow such as reading data in directly from the internet or generating presentation-ready reports and tables directly from their model results.

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