| % File src/library/stats/man/logLik.Rd |
| % Part of the R package, https://www.R-project.org |
| % Copyright 1995-2018 R Core Team |
| % Distributed under GPL 2 or later |
| |
| \name{logLik} |
| \encoding{UTF-8} |
| \alias{logLik} |
| %\alias{print.logLik} |
| %\alias{str.logLik} |
| \alias{logLik.lm} |
| \title{Extract Log-Likelihood} |
| \usage{ |
| logLik(object, \dots) |
| |
| \method{logLik}{lm}(object, REML = FALSE, \dots) |
| } |
| \arguments{ |
| \item{object}{any object from which a log-likelihood value, or a |
| contribution to a log-likelihood value, can be extracted.} |
| \item{\dots}{some methods for this generic function require additional |
| arguments.} |
| \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}.} |
| } |
| \description{ |
| This function is generic; method functions can be written to handle |
| specific classes of objects. Classes which have methods for this |
| function include: \code{"glm"}, \code{"lm"}, \code{"nls"} and |
| \code{"Arima"}. Packages contain methods for other classes, such as |
| \code{"fitdistr"}, \code{"negbin"} and \code{"polr"} in package |
| \CRANpkg{MASS}, \code{"multinom"} in package \CRANpkg{nnet} and |
| \code{"gls"}, \code{"gnls"} \code{"lme"} and others in package |
| \CRANpkg{nlme}. |
| } |
| % \code{corStruct}, \code{lmList}, \code{lmeStruct}, \code{reStruct}, and |
| % \code{varFunc}. |
| \details{ |
| \code{logLik} is most commonly used for a model fitted by maximum |
| likelihood, and some uses, e.g.\sspace{}by \code{\link{AIC}}, assume |
| this. So care is needed where other fit criteria have been used, for |
| example REML (the default for \code{"lme"}). |
| |
| For a \code{"glm"} fit the \code{\link{family}} does not have to |
| specify how to calculate the log-likelihood, so this is based on using |
| the family's \code{aic()} function to compute the AIC. For the |
| \code{\link{gaussian}}, \code{\link{Gamma}} and |
| \code{\link{inverse.gaussian}} families it assumed that the dispersion |
| of the GLM is estimated and 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 does not give the maximized |
| likelihood for \code{"glm"} fits from the Gamma and inverse gaussian |
| families, as the estimate of dispersion used is not the MLE. |
| |
| For \code{"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. That method is only applicable to |
| single-response fits. |
| } |
| \value{ |
| Returns an object of class \code{logLik}. This is a number with at |
| least one attribute, \code{"df"} (\bold{d}egrees of \bold{f}reedom), |
| giving the number of (estimated) parameters in the model. |
| |
| There is a simple \code{print} method for \code{"logLik"} objects. |
| |
| There may be other attributes depending on the method used: see the |
| appropriate documentation. One that is used by several methods is |
| \code{"nobs"}, the number of observations used in estimation (after |
| the restrictions if \code{REML = TRUE}). |
| } |
| \seealso{ |
| \code{\link[nlme:logLik.lme]{logLik.gls}}, \code{\link[nlme]{logLik.lme}}, in |
| package \CRANpkg{nlme}, etc. |
| |
| \code{\link{AIC}} |
| } |
| \references{ |
| For \code{logLik.lm}: |
| |
| Harville, D.A. (1974). |
| Bayesian inference for variance components using only error contrasts. |
| \emph{Biometrika}, \bold{61}, 383--385. |
| \doi{10.2307/2334370}. |
| } |
| \author{ |
| \enc{José}{Jose} Pinheiro and Douglas Bates |
| } |
| \examples{ |
| x <- 1:5 |
| lmx <- lm(x ~ 1) |
| logLik(lmx) # using print.logLik() method |
| utils::str(logLik(lmx)) |
| |
| ## lm method |
| (fm1 <- lm(rating ~ ., data = attitude)) |
| logLik(fm1) |
| logLik(fm1, REML = TRUE) |
| |
| \donttest{utils::data(Orthodont, package = "nlme") |
| fm1 <- lm(distance ~ Sex * age, Orthodont) |
| logLik(fm1) |
| logLik(fm1, REML = TRUE) |
| }} |
| \keyword{models} |