loglinll {bayess} | R Documentation |
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)
[Package bayess version 1.6 Index]