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
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Vignettes of LearnBayes

Name
BayesFactors.Rnw
BinomialInference.Rnw
DiscreteBayes.Rnw
MCMCintro.Rnw
MultilevelModeling.Rnw
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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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