logLik.em.glm: Calculate log-likelihood of the EM model.

In emax.glm: General Tools for Building GLM Expectation-Maximization Models

Description

Calculate log-likelihood of the EM model.

Usage

## S3 method for class 'em.glm'
logLik(object, x, y, weight = c(1), ...)

Arguments

object	A 'em.glm' class returned by the em.glm function.
x	An n-by-p design matrix.
y	A vector of observation of length n.
weight	A n length vector of observation weight terms. This is currently designed to be either the exposure for a Poisson model or the number of trials for a Logistic model.
...	optionally more fitted model objects.

Value

Model log-likelihood.

Examples

x <- model.matrix(~ factor(wool) + factor(tension), warpbreaks)
y <- warpbreaks$breaks
m <- em.glm(x = x, y = y, K = 2, b.init = "random")
logLik(m, x, y)

emax.glm documentation built on July 4, 2019, 5:04 p.m.