# 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! |

## Last month downloads

## 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 |

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