normpostsim {LearnBayes} | R Documentation |
Simulation from Bayesian normal sampling model
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)
[Package LearnBayes version 2.15.1 Index]