Bayesian Regression Models with RStanARM

TJ Mahr
Sept. 21, 2016

Madison R Users Group

Github repository
@tjmahr

Overview

Learning more

You want to learn RStanARM

See the vignettes. There is one for each kind of model.

RStanARM vignettes

You want to learn Stan

The Stan Manual

You are trained in classical regression

'Rethinking'

  • This book is exceptional, stuffed to the brim with trivia, advice, and wisdom.
  • Not just a book about statistics, but how we use statistical models in scientific practice.
  • Explains side issues like MCMC, basics of information theory, or why the normal distribution is so prevalent – but just deep enough for the reader to get the intuitions needed for practice.
  • My sole criticism is that its companion R rethinking package is not on CRAN.

You need puppies on the cover

Kruschke (2015). Doing Bayesian Analysis.

I just got this book, but so far it's approachable and comprehensive, like a statistical cookbook. Many more equations and proofs than in Rethinking.

You study psycholinguistics

You need a reading list and fast

You need to figure out how many socks are in the laundry

  • See Rasmus Bååth's intro to approximate Bayesian inference.
  • Kind of removed from our topic, but entertaining example that emphasizes how Bayesian models are generative.
  • If we are exploring all the plausible ways the data could have been generated, we're probably doing a kind of Bayesian analysis.