logitll: Log-likelihood of the logit model

In bayess: Bayesian Essentials with R

Log-likelihood of the logit model

Description

Direct computation of the logarithm of the likelihood of a standard logit model (Chapter 4)

P(y=1|X,\beta)= \{1+\exp(-\beta^{T}X)\}^{-1}.

Usage

logitll(beta, y, X)

Arguments

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

Value

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

See Also

probitll

Examples

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

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