R: Functions for Learning Bayesian Inference

# Functions for Learning Bayesian Inference

## Documentation for package ‘LearnBayes’ version 2.15.2

- DESCRIPTION file
- Code demos. Use demo() to run them.

## Help Pages

achievement | School achievement data
baseball.1964 | Team records in the 1964 National League baseball season
bayes.influence | Observation sensitivity analysis in beta-binomial model
bayes.model.selection | Bayesian regression model selection using G priors
bayes.probit | Simulates from a probit binary response regression model using data augmentation and Gibbs sampling
bayesresiduals | Computation of posterior residual outlying probabilities for a linear regression model
bermuda.grass | Bermuda grass experiment data
beta.select | Selection of Beta Prior Given Knowledge of Two Quantiles
betabinexch | Log posterior of logit mean and log precision for Binomial/beta exchangeable model
betabinexch0 | Log posterior of mean and precision for Binomial/beta exchangeable model
bfexch | Logarithm of integral of Bayes factor for testing homogeneity of proportions
bfindep | Bayes factor against independence assuming alternatives close to independence
binomial.beta.mix | Computes the posterior for binomial sampling and a mixture of betas prior
birdextinct | Bird measurements from British islands
birthweight | Birthweight regression study
blinreg | Simulation from Bayesian linear regression model
blinregexpected | Simulates values of expected response for linear regression model
blinregpred | Simulates values of predicted response for linear regression model
bprobit.probs | Simulates fitted probabilities for a probit regression model
bradley.terry.post | Log posterior of a Bradley Terry random effects model
breastcancer | Survival experience of women with breast cancer under treatment
calculus.grades | Calculus grades dataset
cancermortality | Cancer mortality data
careertraj.setup | Setup for Career Trajectory Application
cauchyerrorpost | Log posterior of median and log scale parameters for Cauchy sampling
chemotherapy | Chemotherapy treatment effects on ovarian cancer
ctable | Bayes factor against independence using uniform priors
darwin | Darwin's data on plants
discint | Highest probability interval for a discrete distribution
discrete.bayes | Posterior distribution with discrete priors
discrete.bayes.2 | Posterior distribution of two parameters with discrete priors
dmnorm | The probability density function for the multivariate normal (Gaussian) probability distribution
dmt | Probability density function for multivariate t
donner | Donner survival study
election | Florida election data
election.2008 | Poll data from 2008 U.S. Presidential Election
footballscores | Game outcomes and point spreads for American football
gibbs | Metropolis within Gibbs sampling algorithm of a posterior distribution
groupeddatapost | Log posterior of normal parameters when data is in grouped form
hearttransplants | Heart transplant mortality data
hiergibbs | Gibbs sampling for a hierarchical regression model
histprior | Density function of a histogram distribution
howardprior | Logarithm of Howard's dependent prior for two proportions
impsampling | Importance sampling using a t proposal density
indepmetrop | Independence Metropolis independence chain of a posterior distribution
iowagpa | Admissions data for an university
jeter2004 | Hitting data for Derek Jeter
laplace | Summarization of a posterior density by the Laplace method
lbinorm | Logarithm of bivariate normal density
logctablepost | Log posterior of difference and sum of logits in a 2x2 table
logisticpost | Log posterior for a binary response model with a logistic link and a uniform prior
logpoissgamma | Log posterior with Poisson sampling and gamma prior
logpoissnormal | Log posterior with Poisson sampling and normal prior
marathontimes | Marathon running times
mnormt.onesided | Bayesian test of one-sided hypothesis about a normal mean
mnormt.twosided | Bayesian test of a two-sided hypothesis about a normal mean
mycontour | Contour plot of a bivariate density function
normal.normal.mix | Computes the posterior for normal sampling and a mixture of normals prior
normal.select | Selection of Normal Prior Given Knowledge of Two Quantiles
normchi2post | Log posterior density for mean and variance for normal sampling
normnormexch | Log posterior of mean and log standard deviation for Normal/Normal exchangeable model
normpostpred | Posterior predictive simulation from Bayesian normal sampling model
normpostsim | Simulation from Bayesian normal sampling model
ordergibbs | Gibbs sampling for a hierarchical regression model
pbetap | Predictive distribution for a binomial sample with a beta prior
pbetat | Bayesian test of a proportion
pdisc | Posterior distribution for a proportion with discrete priors
pdiscp | Predictive distribution for a binomial sample with a discrete prior
plot.bayes | Posterior distribution with discrete priors
plot.bayes2 | Posterior distribution of two parameters with discrete priors
poissgamexch | Log posterior of Poisson/gamma exchangeable model
poisson.gamma.mix | Computes the posterior for Poisson sampling and a mixture of gammas prior
predplot | Plot of predictive distribution for binomial sampling with a beta prior
print.bayes | Posterior distribution with discrete priors
prior.two.parameters | Construct discrete uniform prior for two parameters
puffin | Bird measurements from British islands
rdirichlet | Random draws from a Dirichlet distribution
reg.gprior.post | Computes the log posterior of a normal regression model with a g prior.
regroup | Collapses a matrix by summing over rows
rejectsampling | Rejecting sampling using a t proposal density
rigamma | Random number generation for inverse gamma distribution
rmnorm | Random number generation for multivariate normal
rmt | Random number generation for multivariate t
robustt | Gibbs sampling for a robust regression model
rtruncated | Simulates from a truncated probability distribution
rwmetrop | Random walk Metropolis algorithm of a posterior distribution
schmidt | Batting data for Mike Schmidt
simcontour | Simulated draws from a bivariate density function on a grid
sir | Sampling importance resampling
sluggerdata | Hitting statistics for ten great baseball players
soccergoals | Goals scored by professional soccer team
stanfordheart | Data from Stanford Heart Transplanation Program
strikeout | Baseball strikeout data
studentdata | Student dataset
summary.bayes | Posterior distribution with discrete priors
transplantpost | Log posterior of a Pareto model for survival data
triplot | Plot of prior, likelihood and posterior for a proportion
weibullregpost | Log posterior of a Weibull proportional odds model for survival data