bayess (version 1.6)

logitll: 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)

Value

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

Arguments

beta

coefficient of the logit model

y

vector of binary response variables

X

covariate matrix

See Also

probitll

Examples

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