Learn R Programming

Bolstad2 (version 1.0-29)

Bolstad Functions

Description

A set of R functions and data sets for the book "Understanding Computational Bayesian Statistics." This book was written by Bill (WM) Bolstad and published in 2009 by John Wiley & Sons (ISBN 978-0470046098).

Copy Link

Version

Install

install.packages('Bolstad2')

Monthly Downloads

523

Version

1.0-29

License

GPL (>= 2)

Issues

0

Pull Requests

0

Stars

1

Forks

0

Maintainer

James Curran

Last Published

April 11th, 2022

Functions in Bolstad2 (1.0-29)

credIntNum

Calculate a credible interval from a numerically specified posterior CDF
chd.df

Coronary Heart Disease Chapter 8 Example 11
BayesCPH

Bayesian Cox Proportional Hazards Modelling
bivnormMH

Metropolis Hastings sampling from a Bivariate Normal distribution
GelmanRubin

Calculate the Gelman Rubin statistic
BayesLogistic

Bayesian Logistic Regression
credInt

Calculate a credible interval 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
c10ex16.df

Chapter 10 Example 16 data
AidsSurvival.df

HIV Survival data
logisticTest.df

Test data for bayesLogistic
hiermeanRegTest.df

Test data for hiermeanReg
thin

Thin an MCMC sample
hierMeanReg

Hierarchical Normal Means Regression Model
pnullSamp

Test a one sided hypothesis using a sample from a posterior density
normGibbs

Draw a sample from a posterior distribution of data with an unknown mean and variance using Gibbs sampling
sintegral

Numerical integration using Simpson's Rule
poissonTest.df

A test data set for bayesPois
credIntSamp

Calculate a credible interval from a numerically specified posterior CDF
BayesPois

Bayesian Pois Regression
describe

Give simple descriptive statistics for a matrix or a data frame
pNull

Test a one sided hypothesis from a numerically specified posterior CDF or from a sample from the posterior
normMixMH

Sample from a normal mixture model using Metropolis-Hastings