gibbsNormal: Gibbs sampler for a normal random sample with a...

In nclbayes: Functions, Demos and Examples of Bayesian Analysis and Basic MCMC

Description

Simulates realisations from the posterior distribution for the mean and precision in a normal distribution based on a random sample and a semi-conjugate prior by using a Gibbs sampler.

Usage

gibbsNormal(N, initial, priorparam, n, xbar, s)

Arguments

N	length of MCMC chain.
initial	starting value for the algorithm.
priorparam	prior parameters b,c,g,h.
n	size of random sample.
xbar	mean of random sample.
s	standard deviation of random sample.

Examples

mcmcAnalysis(gibbsNormal(N=100,initial=c(10,0.25),
 priorparam=c(10,1/100,3,12),n=100,xbar=15,s=4.5),rows=2)

nclbayes documentation built on May 2, 2019, 5:53 p.m.