logLik {stats}R Documentation

Extract Log-Likelihood


This function is generic; method functions can be written to handle specific classes of objects. Classes which already have methods for this function include: glm, lm, nls, Arima and gls, lme and others in package nlme.


logLik(object, ...)

## S3 method for class 'lm':
logLik(object, REML = FALSE, ...)


object any object from which a log-likelihood value, or a contribution to a log-likelihood value, can be extracted.
... some methods for this generic function require additional arguments.
REML an optional logical value. If TRUE the restricted log-likelihood is returned, else, if FALSE, the log-likelihood is returned. Defaults to FALSE.


For a "glm" fit the family does not have to specify how to calculate the log-likelihood, so this is based on the family's aic() function to compute the AIC. For the gaussian, Gamma and inverse.gaussian families it assumed that the dispersion of the GLM is estimated has been counted as a parameter in the AIC value, and for all other families it is assumed that the dispersion is known.

Note that this procedure is not completely accurate for the gamma and inverse gaussian families, as the estimate of dispersion used is not the MLE.

For "lm" fits it is assumed that the scale has been estimated (by maximum likelihood or REML), and all the constants in the log-likelihood are included.


Returns an object, say r, of class logLik which is a number with attributes, attr(r, "df") (degrees of freedom) giving the number of (estimated) parameters in the model. There is a simple print method for logLik objects.
The details depend on the method function used; see the appropriate documentation.


Jose Pinheiro and Douglas Bates


For logLik.lm:

Harville, D.A. (1974). Bayesian inference for variance components using only error contrasts. Biometrika, 61, 383–385.

See Also

logLik.gls, logLik.lme, in package nlme, etc.


x <- 1:5
lmx <- lm(x ~ 1)
logLik(lmx) # using print.logLik() method

## lm method
(fm1 <- lm(rating ~ ., data = attitude))
logLik(fm1, REML = TRUE)

res <- try(data(Orthodont, package="nlme"))
if(!inherits(res, "try-error")) {
  fm1 <- lm(distance ~ Sex * age, Orthodont)
  print(logLik(fm1, REML = TRUE))

[Package stats version 2.5.0 Index]