loglinnoinflpost: Log of the posterior density for the log-linear model under a...

In bayess: Bayesian Essentials with R

Log of the posterior density for the log-linear model under a noninformative prior

Description

This function computes the logarithm of the posterior density associated with a log-linear model and the noninformative prior used in Chapter 4.

Usage

loglinnoinflpost(beta, y, X)

Arguments

beta	parameter of the log-linear model
y	binary response variable
X	covariate matrix

Details

This function does not test for coherence between the lengths of y, X and beta, hence may return an error message in case of incoherence.

Value

returns the logarithm of the logit posterior density for the data y, covariate matrix X and parameter vector beta

Examples

X=matrix(rnorm(20*3),ncol=3)
beta=c(3,-2,1)
y=rpois(20,exp(X%*%beta))
loglinnoinflpost(beta, y, X) 

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