# LearnBayes v2.15.1

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## Functions for Learning Bayesian Inference

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

## Functions in LearnBayes

 Name Description bayes.model.selection Bayesian regression model selection using G priors betabinexch Log posterior of logit mean and log precision for Binomial/beta exchangeable model baseball.1964 Team records in the 1964 National League baseball season bayes.probit Simulates from a probit binary response regression model using data augmentation and Gibbs sampling bermuda.grass Bermuda grass experiment data blinregexpected Simulates values of expected response for linear regression model betabinexch0 Log posterior of mean and precision for Binomial/beta exchangeable model binomial.beta.mix Computes the posterior for binomial sampling and a mixture of betas prior bayesresiduals Computation of posterior residual outlying probabilities for a linear regression model blinregpred Simulates values of predicted response for linear regression model bfexch Logarithm of integral of Bayes factor for testing homogeneity of proportions beta.select Selection of Beta Prior Given Knowledge of Two Quantiles birdextinct Bird measurements from British islands bfindep Bayes factor against independence assuming alternatives close to independence bprobit.probs Simulates fitted probabilities for a probit regression model achievement School achievement data cauchyerrorpost Log posterior of median and log scale parameters for Cauchy sampling bradley.terry.post Log posterior of a Bradley Terry random effects model breastcancer Survival experience of women with breast cancer under treatment bayes.influence Observation sensitivity analysis in beta-binomial model ctable Bayes factor against independence using uniform priors chemotherapy Chemotherapy treatment effects on ovarian cancer calculus.grades Calculus grades dataset darwin Darwin's data on plants discint Highest probability interval for a discrete distribution groupeddatapost Log posterior of normal parameters when data is in grouped form dmt Probability density function for multivariate t birthweight Birthweight regression study discrete.bayes.2 Posterior distribution of two parameters with discrete priors hearttransplants Heart transplant mortality data donner Donner survival study jeter2004 Hitting data for Derek Jeter hiergibbs Gibbs sampling for a hierarchical regression model blinreg Simulation from Bayesian linear regression model laplace Summarization of a posterior density by the Laplace method logpoissnormal Log posterior with Poisson sampling and normal prior normal.select Selection of Normal Prior Given Knowledge of Two Quantiles histprior Density function of a histogram distribution election.2008 Poll data from 2008 U.S. Presidential Election marathontimes Marathon running times normchi2post Log posterior density for mean and variance for normal sampling election Florida election data cancermortality Cancer mortality data indepmetrop Independence Metropolis independence chain of a posterior distribution normpostsim Simulation from Bayesian normal sampling model pdisc Posterior distribution for a proportion with discrete priors careertraj.setup Setup for Career Trajectory Application iowagpa Admissions data for an university ordergibbs Gibbs sampling for a hierarchical regression model pdiscp Predictive distribution for a binomial sample with a discrete prior mycontour Contour plot of a bivariate density function discrete.bayes Posterior distribution with discrete priors mnormt.onesided Bayesian test of one-sided hypothesis about a normal mean normal.normal.mix Computes the posterior for normal sampling and a mixture of normals prior rmnorm Random number generation for multivariate normal dmnorm The probability density function for the multivariate normal (Gaussian) probability distribution footballscores Game outcomes and point spreads for American football mnormt.twosided Bayesian test of a two-sided hypothesis about a normal mean rmt Random number generation for multivariate t lbinorm Logarithm of bivariate normal density gibbs Metropolis within Gibbs sampling algorithm of a posterior distribution rwmetrop Random walk Metropolis algorithm of a posterior distribution poissgamexch Log posterior of Poisson/gamma exchangeable model howardprior Logarithm of Howard's dependent prior for two proportions logctablepost Log posterior of difference and sum of logits in a 2x2 table schmidt Batting data for Mike Schmidt impsampling Importance sampling using a t proposal density poisson.gamma.mix Computes the posterior for Poisson sampling and a mixture of gammas prior studentdata Student dataset logisticpost Log posterior for a binary response model with a logistic link and a uniform prior normnormexch Log posterior of mean and log standard deviation for Normal/Normal exchangeable model rejectsampling Rejecting sampling using a t proposal density transplantpost Log posterior of a Pareto model for survival data normpostpred Posterior predictive simulation from Bayesian normal sampling model logpoissgamma Log posterior with Poisson sampling and gamma prior sir Sampling importance resampling predplot Plot of predictive distribution for binomial sampling with a beta prior rigamma Random number generation for inverse gamma distribution pbetap Predictive distribution for a binomial sample with a beta prior prior.two.parameters Construct discrete uniform prior for two parameters regroup Collapses a matrix by summing over rows sluggerdata Hitting statistics for ten great baseball players pbetat Bayesian test of a proportion soccergoals Goals scored by professional soccer team robustt Gibbs sampling for a robust regression model reg.gprior.post Computes the log posterior of a normal regression model with a g prior. rtruncated Simulates from a truncated probability distribution stanfordheart Data from Stanford Heart Transplanation Program puffin Bird measurements from British islands strikeout Baseball strikeout data rdirichlet Random draws from a Dirichlet distribution triplot Plot of prior, likelihood and posterior for a proportion simcontour Simulated draws from a bivariate density function on a grid weibullregpost Log posterior of a Weibull proportional odds model for survival data No Results!

## Vignettes of LearnBayes

 Name BayesFactors.Rnw BinomialInference.Rnw DiscreteBayes.Rnw MCMCintro.Rnw MultilevelModeling.Rnw No Results!

## Details

 Type Package Date 2018-03-18 LazyData yes License GPL (>= 2) Packaged 2018-03-18 17:46:55 UTC; jamesalbert NeedsCompilation no Repository CRAN Date/Publication 2018-03-18 20:41:13 UTC
 Contributors Jim Albert