The R Project SVN R

\name{logLik.lm}
\alias{logLik.lm}
\title{Extract Log-Likelihood from an lm Object}
\usage{
\method{logLik}{lm}(object, REML = FALSE, \dots)
}
\arguments{
  \item{object}{an object inheriting from class \code{"lm"}.}
  \item{REML}{an optional logical value.  If \code{TRUE} the restricted
    log-likelihood is returned, else, if \code{FALSE}, the
    log-likelihood is returned.  Defaults to \code{FALSE}.}
  \item{\dots}{further arguments to be passed to or from methods.}
}
\description{
  If \code{REML = FALSE}, returns the log-likelihood value of the linear
  model represented by \code{object} evaluated at the estimated
  coefficients; else, the restricted log-likelihood evaluated at the
  estimated coefficients is returned.
}
\value{
  an object of class \code{logLik},
  the (restricted) log-likelihood of the linear model represented by
  \code{object} evaluated at the estimated coefficients.  Note that
  error variance \eqn{\sigma^2} is estimated in \code{lm()} and hence
  counted as well.
}
\references{
  Harville, D.A. (1974).
  Bayesian inference for variance components using only error contrasts.
  \emph{Biometrika}, \bold{61}, 383--385.
}
\author{Jose Pinheiro and Douglas Bates}
\seealso{\code{\link{lm}}}
\examples{
data(attitude)
(fm1 <- lm(rating ~ ., data = attitude))
logLik(fm1)
logLik(fm1, REML = TRUE)


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