normpostsim: Simulation from Bayesian normal sampling model

In LearnBayes: Functions for Learning Bayesian Inference

Description

Gives a simulated sample from the joint posterior distribution of the mean and variance for a normal sampling prior with a noninformative or informative prior. The prior assumes mu and sigma2 are independent with mu assigned a normal prior with mean mu0 and variance tau2, and sigma2 is assigned a inverse gamma prior with parameters a and b.

Usage

normpostsim(data,prior=NULL,m=1000)

Arguments

data	vector of observations
prior	list with components mu, a vector with the prior mean and variance, and sigma2, a vector of the inverse gamma parameters
m	number of simulations desired

Value

mu	vector of simulated draws of normal mean
sigma2	vector of simulated draws of normal variance

Author(s)

Jim Albert

Examples

data(darwin)
s=normpostsim(darwin$difference)

Example output

LearnBayes documentation built on May 1, 2019, 7:03 p.m.