BayesReg: Bayesian linear regression output

In bayess: Bayesian Essentials with R

Bayesian linear regression output

Description

This function contains the R code for the implementation of Zellner's G-prior analysis of the regression model as described in Chapter 3. The purpose of BayesRef is dual: first, this R function shows how easily automated this approach can be. Second, it also illustrates how it is possible to get exactly the same type of output as the standard R function summary(lm(y~X)). In particular, it calculates the Bayes factors for variable selection, more precisely single variable exclusion.

Usage

BayesReg(y, X, g = length(y), betatilde = rep(0, dim(X)[2]), prt = TRUE)

Arguments

y	response variable
X	matrix of regressors
g	constant g for the G-prior
betatilde	prior mean on beta
prt	boolean variable for printing out the standard output

Value

postmeancoeff	posterior mean of the regression coefficients
postsqrtcoeff	posterior standard deviation of the regression coefficients
log10bf	log-Bayes factors against the full model
postmeansigma2	posterior mean of the variance of the model
postvarsigma2	posterior variance of the variance of the model

Examples

data(faithful)
BayesReg(faithful[,1],faithful[,2])

bayess documentation built on Aug. 11, 2022, 5:07 p.m.