AidsSurvival.df         HIV Survival data
BayesCPH                Bayesian Cox Proportional Hazards Modelling
BayesLogistic           Bayesian Logistic Regression
BayesPois               Bayesian Pois Regression
GelmanRubin             Calculate the Gelman Rubin statistic
bivnormMH               Metropolis Hastings sampling from a Bivariate
                        Normal distribution
c10ex16.df              Chapter 10 Example 16 data
chd.df                  Coronary Heart Disease Chapter 8 Example 11
credInt                 Calculate a credible interval from a
                        numerically specified posterior CDF or from a
                        sample from the posterior
credIntNum              Calculate a credible interval from a
                        numerically specified posterior CDF
credIntSamp             Calculate a credible interval from a
                        numerically specified posterior CDF
describe                Give simple descriptive statistics for a matrix
                        or a data frame
hierMeanReg             Hierarchical Normal Means Regression Model
hiermeanRegTest.df      Test data for hiermeanReg
logisticTest.df         Test data for bayesLogistic
normGibbs               Draw a sample from a posterior distribution of
                        data with an unknown mean and variance using
                        Gibbs sampling
normMixMH               Sample from a normal mixture model using
                        Metropolis-Hastings
pNull                   Test a one sided hypothesis from a numerically
                        specified posterior CDF or from a sample from
                        the posterior
pnullNum                Test a one sided hypothesis from a numerically
                        specified posterior CDF
pnullSamp               Test a one sided hypothesis using a sample from
                        a posterior density
poissonTest.df          A test data set for bayesPois
sintegral               Numerical integration using Simpson's Rule
thin                    Thin an MCMC sample
