Bayesian Analysis of Correlated Proportions Using Stan in R
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By: Jay Harrison
Stan (https://mc-stan.org/) is a platform that performs Bayesian MCMC analyses using Hamiltonian Monte Carlo, a fast, efficient posterior sampling algorithm. This talk will illustrate the use of Stan within an R script to analyze a small data set involving correlated proportions from a pet food preference experiment.
The talk will include using the zCompositions package (https://cran.r-project.org/package=zCompositions) to prepare data with small proportions having left-censoring. It will also show two ways of performing symbolic algebraic manipulations for an intermediate step.
The meetup will be in The Showroom in the CIC building at 20 South Sarah Street, St. Louis, MO 63108. The building entrance is at the corner of Forest Park Avenue and Sarah Street. You can find directions at http://stl.cic.us/directions/ (CIC@CET).
We will meet for snacks, set-up, and conversation at 6:00PM. The presentation will start at 6:30PM and will be about 60 minutes long.