BayesComputeR

This R Markdown documents and associated datasets are used for a short course "Bayesian Thinking: Fundamentals, Computation, and Multilevel Modeling" by Jim Albert, Bowling Green State University

Packages -- the following packages available from CRAN are used in these examples and should be installed at first

• arm - Data Analysis Using Multilevel/Hierarchical Models
• BayesTestStreak (available from GitHub) - Testing Streakiness in Binary Sequences
• betareg - Beta Regression
• brms - Bayesian Regression Models using 'Stan'
• coda - Output Analysis and Diagnostics for MCMC
• lme4 - Linear Mixed-Effects Models using 'Eigen' and S4
• LearnBayes - Functions for Learning Bayesian Inference
• rethinking - Statistical Rethinking book package
• rjags - Bayesian Graphical Models using MCMC (JAGS software also needs to be installed)
• rstanarm - Bayesian Applied Regression Modeling via Stan
• TeachBayes - Teaching Bayesian Inference
• tidybayes - Tidy Data and 'Geoms' for Bayesian Models
• tidyverse - suite of packages of the Tidyverse

Part I - Basic Bayes

• Streakiness.Rmd -- learning about a geometric proportion
• Moving_to_NC -- learning about a normal mean with known standard deviation
• NormalSampling.Rmd - normal sampling model
• SelectedData.Rmd -- learning about a normal mean observing selected order statistics
• Intro_to_JAGS.Rmd -- illustration of JAGS for a Poisson log-linear model

Part II - Regression

• Regression.Rmd -- Bayesian linear regression
• Worship Data.Rmd - Modeling counts by a Poisson log linear model
• Attendance.Rmd - Modeling fractions of capacity attendance using a beta regression model

Part III - Multilevel Modeling

• HomeRun.Rmd -- Modeling home run rates using a varying intercept model
• BBS_Survey.Rmd -- Multilevel estimate of some trend estimates
• Coffee_Shop.Rmd - Modeling varying intercepts and varying slopes for waiting times