loglinll: Log of the likelihood of the log-linear model

In bayess: Bayesian Essentials with R

Log of the likelihood of the log-linear model

Description

This function provides a direct computation of the logarithm of the likelihood of a standard log-linear model, as defined in Chapter 4.

Usage

loglinll(beta, y, X)

Arguments

beta	coefficient of the logit model
y	vector of binary response variables
X	covariate matrix

Value

returns the logarithmic value of the logit likelihood 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))
loglinll(beta, y, X)

bayess documentation built on May 29, 2024, 3:58 a.m.