blinregexpected

Simulates draws of the posterior distribution of an expected response for
a linear regression model with a noninformative 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

blinregexpected function

<dl> <dt>X1</dt>
<dd>matrix where each row corresponds to a covariate set</dd> <dt>theta.sample</dt>
<dd>list with components beta, matrix of simulated draws of regression vector,
and sigma, vector of simulated draws of sampling error standard deviation</dd></dl>

Arguments

Author

Simulates values of expected response for linear regression model — blinregexpected

<dl>

 <dt>X1</dt>
<dd>matrix where each row corresponds to a covariate set</dd>

 <dt>theta.sample</dt>
<dd>list with components beta, matrix of simulated draws of regression vector,
and sigma, vector of simulated draws of sampling error standard deviation</dd>

</dl>

blinregexpected: Simulates values of expected response for linear regression model

Description

Usage

Value

Arguments

Author

Examples