Category | Chapter | Name | Description | |||||||

data | Chapter 1 | studentdata | Student dataset | |||||||

one parameter | Chapter 2 | beta.select | Selection of Beta Prior Given Knowledge of Two Quantiles | |||||||

one parameter | Chapter 2 | discint | Highest probability interval for a discrete distribution | |||||||

one parameter | Chapter 2 | histprior | Density function of a histogram distribution | |||||||

one parameter | Chapter 2 | pbetap | Predictive distribution for a binomial sample with a beta prior | |||||||

one parameter | Chapter 2 | pdisc | Posterior distribution for a proportion with discrete priors | |||||||

one parameter | Chapter 2 | pdiscp | Predictive distribution for a binomial sample with a discrete prior | |||||||

one parameter | Chapter 3 | binomial.beta.mix | Computes the posterior for binomial sampling and a mixture of betas prior | |||||||

data | Chapter 3 | footballscores | Game outcomes and point spreads for American football | |||||||

one parameter | Chapter 3 | normal.select | Selection of Normal Prior Given Knowledge of Two Quantiles | |||||||

testing | Chapter 3 | pbetat | Bayesian test of a proportion | |||||||

one parameter | Chapter 3 | poisson.gamma.mi | Computes the posterior for Poisson sampling and a mixture of gammas prior | |||||||

data | Chapter 4 | election.2008 | Poll data from 2008 U.S. Presidential Election | |||||||

model | Chapter 4 | howardprior | Logarithm of Howard's dependent prior for two proportions | |||||||

model | Chapter 4 | logisticpost | Log posterior for a binary response model with a logistic link and a uniform prior | |||||||

data | Chapter 4 | marathontimes | Marathon running times | |||||||

two parameters | Chapter 4 | mycontour | Contour plot of a bivariate density function | |||||||

model | Chapter 4 | normchi2post | Log posterior density for mean and variance for normal sampling | |||||||

two parameters | Chapter 4 | normpostsim | Simulation from Bayesian normal sampling model | |||||||

utility | Chapter 4 | rdirichlet | Random draws from a Dirichlet distribution | |||||||

two parameters | Chapter 4 | simcontour | Simulated draws from a bivariate density function on a grid | |||||||

model | Chapter 5 | bayes.influence | Observation sensitivity analysis in beta-binomial model | |||||||

model | Chapter 5 | betabinexch | Log posterior of logit mean and log precision for Binomial/beta exchangeable model | |||||||

model | Chapter 5 | betabinexch0 | Log posterior of mean and precision for Binomial/beta exchangeable model | |||||||

data | Chapter 5 | cancermortality | Cancer mortality data | |||||||

utility | Chapter 5 | dmt | Probability density function for multivariate t | |||||||

general | Chapter 5 | impsampling | Importance sampling using a t proposal density | |||||||

general | Chapter 5 | laplace | Summarization of a posterior density by the Laplace method | |||||||

utility | Chapter 5 | lbinorm | Logarithm of bivariate normal density | |||||||

general | Chapter 5 | rejectsampling | Rejecting sampling using a t proposal density | |||||||

utility | Chapter 5 | rmt | Random number generation for multivariate t | |||||||

general | Chapter 5 | sir | Sampling importance resampling | |||||||

model | Chapter 6 | cauchyerrorpost | Log posterior of median and log scale parameters for Cauchy sampling | |||||||

general | Chapter 6 | gibbs | Metropolis within Gibbs sampling algorithm of a posterior distribution | |||||||

model | Chapter 6 | groupeddatapost | Log posterior of normal parameters when data is in grouped form | |||||||

general | Chapter 6 | indepmetrop | Independence Metropolis independence chain of a posterior distribution | |||||||

general | Chapter 6 | rwmetrop | Random walk Metropolis algorithm of a posterior distribution | |||||||

data | Chapter 6 | stanfordheart | Data from Stanford Heart Transplanation Program | |||||||

model | Chapter 6 | transplantpost | Log posterior of a Pareto model for survival data | |||||||

data | Chapter 7 | hearttransplants | Heart transplant mortality data | |||||||

model | Chapter 7 | normnormexch | Log posterior of mean and log standard deviation for Normal/Normal exchangeable model | |||||||

model | Chapter 7 | poissgamexch | Log posterior of Poisson/gamma exchangeable model | |||||||

testing | Chapter 8 | bfexch | Logarithm of integral of Bayes factor for testing homogeneity of proportions | |||||||

testing | Chapter 8 | bfindep | Bayes factor against independence assuming alternatives close to independence | |||||||

testing | Chapter 8 | ctable | Bayes factor against independence using uniform priors | |||||||

data | Chapter 8 | jeter2004 | Hitting data for Derek Jeter | |||||||

model | Chapter 8 | logpoissgamma | Log posterior with Poisson sampling and gamma prior | |||||||

model | Chapter 8 | logpoissnormal | Log posterior with Poisson sampling and normal prior | |||||||

testing | Chapter 8 | mnormt.onesided | Bayesian test of one-sided hypothesis about a normal mean | |||||||

testing | Chapter 8 | mnormt.twosided | Bayesian test of a two-sided hypothesis about a normal mean | |||||||

utility | Chapter 8 | regroup | Collapses a matrix by summing over rows | |||||||

data | Chapter 8 | soccergoals | Goals scored by professional soccer team | |||||||

data | Chapter 9 | achievement | School achievement data | |||||||

data | Chapter 9 | baseball.1964 | Team records in the 1964 National League baseball season | |||||||

regression | Chapter 9 | bayes.model.selecti | Bayesian regression model selection using G priors | |||||||

regression | Chapter 9 | bayesresiduals | Computation of posterior residual outlying probabilities for a linear regression model | |||||||

data | Chapter 9 | birdextinct | Bird measurements from British islands | |||||||

data | Chapter 9 | birthweight | Birthweight regression study | |||||||

regression | Chapter 9 | blinreg | Simulation from Bayesian linear regression model | |||||||

regression | Chapter 9 | blinregexpected | Simulates values of expected response for linear regression model | |||||||

regression | Chapter 9 | blinregpred | Simulates values of predicted response for linear regression model | |||||||

model | Chapter 9 | bradley.terry.post | Log posterior of a Bradley Terry random effects model | |||||||

data | Chapter 9 | breastcancer | Survival experience of women with breast cancer under treatment | |||||||

data | Chapter 9 | chemotherapy | Chemotherapy treatment effects on ovarian cancer | |||||||

utility | Chapter 9 | dmnorm | The probability density function for the multivariate normal (Gaussian) probability distribution | |||||||

data | Chapter 9 | puffin | Bird measurements from British islands | |||||||

regression | Chapter 9 | reg.gprior.post | Computes the log posterior of a normal regression model with a g prior. | |||||||

utility | Chapter 9 | rigamma | Random number generation for inverse gamma distribution | |||||||

utility | Chapter 9 | rmnorm | Random number generation for multivariate normal | |||||||

data | Chapter 9 | schmidt | Batting data for Mike Schmidt | |||||||

regression | Chapter 9 | weibullregpost | Log posterior of a Weibull proportional odds model for survival data | |||||||

regression | Chapter 10 | bayes.probit | Simulates from a probit binary response regression model using data augmentation and G | |||||||

regression | Chapter 10 | bprobit.probs | Simulates fitted probabilities for a probit regression model | |||||||

data | Chapter 10 | calculus.grades | Calculus grades dataset | |||||||

data | Chapter 10 | darwin | Darwin's data on plants | |||||||

data | Chapter 10 | donner | Donner survival study | |||||||

data | Chapter 10 | election | Florida election data | |||||||

regression | Chapter 10 | hiergibbs | Gibbs sampling for a hierarchical regression model | |||||||

data | Chapter 10 | iowagpa | Admissions data for an university | |||||||

model | Chapter 10 | ordergibbs | Gibbs sampling for a hierarchical regression model | |||||||

model | Chapter 10 | robustt | Gibbs sampling for a robust regression model | |||||||

data | Chapter 11 | bermuda.grass | Bermuda grass experiment data | |||||||

utility | Chapter 11 | careertraj.setup | Setup for Career Trajectory Application | |||||||

data | Chapter 11 | sluggerdata | Hitting statistics for ten great baseball players | |||||||

one parameter | Not in book | discrete.bayes | Posterior distribution with discrete priors | |||||||

two parameters | Not in book | discrete.bayes.2 | Posterior distribution of two parameters with discrete priors | |||||||

model | Not in book | logctablepost | Log posterior of difference and sum of logits in a 2x2 table | |||||||

one parameter | Not in book | normal.normal.mix | Computes the posterior for normal sampling and a mixture of normals prior | |||||||

two parameters | Not in book | normpostpred | Posterior predictive simulation from Bayesian normal sampling model | |||||||

one parameter | Not in book | plot.bayes | Posterior distribution with discrete priors | |||||||

two parameters | Not in book | plot.bayes2 | Posterior distribution of two parameters with discrete priors | |||||||

one parameter | Not in book | predplot | Plot of predictive distribution for binomial sampling with a beta prior | |||||||

one parameter | Not in book | print.bayes | Posterior distribution with discrete priors | |||||||

two parameters | Not in book | prior.two.paramete | Construct discrete uniform prior for two parameters | |||||||

utility | Not in book | rtruncated | Simulates from a truncated probability distribution | |||||||

data | Not in book | strikeout | Baseball strikeout data | |||||||

one parameter | Not in book | summary.bayes | Posterior distribution with discrete priors | |||||||

one parameter | Not in book | triplot | Plot of prior, likelihood and posterior for a proportion |