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LearnBayes (version 2.15.2)

Functions for Learning Bayesian Inference

Description

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.

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Install

install.packages('LearnBayes')

Monthly Downloads

11,440

Version

2.15.2

License

GPL (>= 2)

Maintainer

Jim Albert

Last Published

January 31st, 2026

Functions in LearnBayes (2.15.2)

Highest probability interval for a discrete distribution

discrete.bayes.2

Posterior distribution of two parameters with discrete priors

Posterior distribution with discrete priors

Florida election data

Birthweight regression study

Simulation from Bayesian linear regression model

cancermortality

Cancer mortality data

Logarithm of bivariate normal density

Poll data from 2008 U.S. Presidential Election

careertraj.setup

Setup for Career Trajectory Application

Gibbs sampling for a hierarchical regression model

The probability density function for the multivariate normal (Gaussian) probability distribution

Donner survival study

Probability density function for multivariate t

Density function of a histogram distribution

Log posterior of difference and sum of logits in a 2x2 table

Summarization of a posterior density by the Laplace method

normal.normal.mix

Computes the posterior for normal sampling and a mixture of normals prior

Contour plot of a bivariate density function

Hitting data for Derek Jeter

bradley.terry.post

Log posterior of a Bradley Terry random effects model

Log posterior of mean and log standard deviation for Normal/Normal exchangeable model

Survival experience of women with breast cancer under treatment

groupeddatapost

Log posterior of normal parameters when data is in grouped form

Logarithm of Howard's dependent prior for two proportions

Random draws from a Dirichlet distribution

calculus.grades

Calculus grades dataset

hearttransplants

Heart transplant mortality data

Bayesian test of a proportion

Log posterior for a binary response model with a logistic link and a uniform prior

Predictive distribution for a binomial sample with a beta prior

Metropolis within Gibbs sampling algorithm of a posterior distribution

Bird measurements from British islands

Game outcomes and point spreads for American football

Log posterior with Poisson sampling and gamma prior

Marathon running times

Posterior predictive simulation from Bayesian normal sampling model

reg.gprior.post

Computes the log posterior of a normal regression model with a g prior.

Collapses a matrix by summing over rows

mnormt.onesided

Bayesian test of one-sided hypothesis about a normal mean

Log posterior of Poisson/gamma exchangeable model

Log posterior with Poisson sampling and normal prior

Importance sampling using a t proposal density

poisson.gamma.mix

Computes the posterior for Poisson sampling and a mixture of gammas prior

blinregexpected

Simulates values of expected response for linear regression model

Simulates values of predicted response for linear regression model

mnormt.twosided

Bayesian test of a two-sided hypothesis about a normal mean

Gibbs sampling for a hierarchical regression model

Random number generation for multivariate normal

Simulation from Bayesian normal sampling model

Random number generation for multivariate t

Gibbs sampling for a robust regression model

Hitting statistics for ten great baseball players

Simulates from a truncated probability distribution

Rejecting sampling using a t proposal density

Random number generation for inverse gamma distribution

Goals scored by professional soccer team

Baseball strikeout data

Independence Metropolis independence chain of a posterior distribution

cauchyerrorpost

Log posterior of median and log scale parameters for Cauchy sampling

Admissions data for an university

Data from Stanford Heart Transplanation Program

Selection of Normal Prior Given Knowledge of Two Quantiles

Chemotherapy treatment effects on ovarian cancer

Log posterior density for mean and variance for normal sampling

Posterior distribution for a proportion with discrete priors

Simulated draws from a bivariate density function on a grid

Random walk Metropolis algorithm of a posterior distribution

Batting data for Mike Schmidt

Plot of predictive distribution for binomial sampling with a beta prior

prior.two.parameters

Construct discrete uniform prior for two parameters

Predictive distribution for a binomial sample with a discrete prior

Student dataset

Log posterior of a Weibull proportional odds model for survival data

Sampling importance resampling

Plot of prior, likelihood and posterior for a proportion

Log posterior of a Pareto model for survival data

bayes.influence

Observation sensitivity analysis in beta-binomial model

School achievement data

Log posterior of logit mean and log precision for Binomial/beta exchangeable model

Log posterior of mean and precision for Binomial/beta exchangeable model

Logarithm of integral of Bayes factor for testing homogeneity of proportions

Selection of Beta Prior Given Knowledge of Two Quantiles

Simulates from a probit binary response regression model using data augmentation and Gibbs sampling

bayes.model.selection

Bayesian regression model selection using G priors

Simulates fitted probabilities for a probit regression model

Team records in the 1964 National League baseball season

Bayes factor against independence assuming alternatives close to independence

Computation of posterior residual outlying probabilities for a linear regression model

Bermuda grass experiment data

Bayes factor against independence using uniform priors

Bird measurements from British islands

binomial.beta.mix

Computes the posterior for binomial sampling and a mixture of betas prior

Darwin's data on plants