logitnoinflpost: Log of the posterior distribution for the probit model under...

In bayess: Bayesian Essentials with R

Log of the posterior distribution for the probit model under a noninformative prior

Description

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

Usage

logitnoinflpost(beta, y, X)

Arguments

beta	parameter of the logit model
y	binary response variable
X	covariate matrix

Value

returns the logarithm of the logit likelihood for the data y, covariate matrix X and parameter beta

See Also

probitnoinflpost

Examples

data(bank)
y=bank[,5]
X=as.matrix(bank[,-5])
logitnoinflpost(runif(4),y,X)

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