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Data Analysis with R, Second Edition - Second Edition

You're reading from Data Analysis with R, Second Edition - Second Edition

Product type Book

Published in Mar 2018

Publisher Packt

ISBN-13 9781788393720

Pages 570 pages

Edition 2nd Edition

Languages

Concepts

Table of Contents (24) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. RefresheR

2. The Shape of Data

3. Describing Relationships

4. Probability

5. Using Data To Reason About The World

6. Testing Hypotheses

7. Bayesian Methods

8. The Bootstrap

9. Predicting Continuous Variables

10. Predicting Categorical Variables

11. Predicting Changes with Time

12. Sources of Data

13. Dealing with Missing Data

14. Dealing with Messy Data

15. Dealing with Large Data

16. Working with Popular R Packages

17. Reproducibility and Best Practices

1. Other Books You May Enjoy

Leave a review - let other readers know what you think

Index

Using JAGS and runjags

Although it's a bit silly to break out MCMC for the single-parameter career recommendation analysis that we discussed earlier, applying this method to this simple example will aid in understanding its usage for more complicated models.

In order to get started, you need to install a software program called JAGS, which stands for Just Another Gibbs Sampler (a Gibbs sampler is a type of MCMC sampler). This program is independent of R, but we will be using R packages to communicate with it. After installing JAGS, you will need to install the R packages rjags, runjags, and modeest. As a reminder, you can install all three with this command:

 > install.packages(c("rjags", "runjags", "modeest"))

To make sure everything is installed properly, load the runjags package, and run the function testjags(). My output looks something like this:

  > library(runjags) 
  > testjags() 
  You are using R version 3.2.1 (2015-06-18) on a unix machine, 
  with the RStudio GUI 
  The...

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