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Bolstad (version 0.2-41)

Functions for Elementary Bayesian Inference

Description

A set of R functions and data sets for the book Introduction to Bayesian Statistics, Bolstad, W.M. (2017), John Wiley & Sons ISBN 978-1-118-09156-2.

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Version

Install

install.packages('Bolstad')

Monthly Downloads

1,509

Version

0.2-41

License

GPL (>= 2)

Maintainer

James Curran

Last Published

October 5th, 2020

Functions in Bolstad (0.2-41)

Bolstad-package

Bolstad Functions
cdf

Cumulative distribution function generic
binobp

Binomial sampling with a beta prior
bayes.lm

Bayesian inference for multiple linear regression
binodp

Binomial sampling with a discrete prior
bayes.lin.reg

Bayesian inference for simple linear regression
lines.Bolstad

Lines method for Bolstad objects
mean.Bolstad

Calculate the posterior mean
createPrior

Create prior generic
poisdp

Poisson sampling with a discrete prior
sd.Bolstad

Posterior standard deviation
normmixp

Bayesian inference on a normal mean with a mixture of normal priors
sd

Standard deviation generic
normnp

Bayesian inference on a normal mean with a normal prior
poisgamp

Poisson sampling with a gamma prior
bayes.t.test

Bayesian t-test
IQR

Interquartile Range generic
moisture.df

Moisture data
bears

bears
print.sscsamp

Print method for objects of class sscsample
poisgcp

Poisson sampling with a general continuous prior
mvnmvnp

Bayesian inference on a mutlivariate normal (MVN) mean with a multivariate normal (MVN) prior
quantile.Bolstad

Posterior quantiles
Bolstad.control

Control Bolstad functions
print.Bolstad

Print method for objects of class Bolstad
sscsample

Simple, Stratified and Cluster Sampling
as.data.frame.Bolstad

as.data.frame.Bolstad
createPrior.default

Create prior default method
decomp

Plot the prior, likelihood, and posterior on the same plot.
slug

Slug data
normdp

Bayesian inference on a normal mean with a discrete prior
sscsample.data

Data for simple random sampling, stratified sampling, and clusting sampling experiments
normgcp

Bayesian inference on a normal mean with a general continuous prior
sintegral

Numerical integration using Simpson's Rule
binomixp

Binomial sampling with a beta mixture prior
binogcp

Binomial sampling with a general continuous prior
nvaricp

Bayesian inference for a normal standard deviation with a scaled inverse chi-squared distribution
plot.Bolstad

Plot method for objects of type Bolstad
summary.Bolstad

Summarizing Bayesian Multiple Linear Regression
var

Variance generic
xdesign

Monte Carlo study of randomized and blocked designs