blinreg

Gives a simulated sample from the joint posterior distribution of the regression
vector and the error standard deviation for a linear regression model with a 
 noninformative or g prior.

models

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

blinreg function

<dl> <dt>y</dt>
<dd>vector of responses</dd> <dt>X</dt>
<dd>design matrix</dd> <dt>m</dt>
<dd>number of simulations desired</dd> <dt>prior</dt>
<dd>list with components c0 and beta0 of Zellner's g prior</dd></dl>

Arguments

Author

Simulation from Bayesian linear regression model — blinreg

<dl>

 <dt>y</dt>
<dd>vector of responses</dd>

 <dt>X</dt>
<dd>design matrix</dd>

 <dt>m</dt>
<dd>number of simulations desired</dd>

 <dt>prior</dt>
<dd>list with components c0 and beta0 of Zellner's g prior</dd>

</dl>

blinreg: Simulation from Bayesian linear regression model

Description

Usage

Value

Arguments

Author

Examples