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% file MASS/boxcox.d
% copyright (C) 1994-2005 W. N. Venables and B. D. Ripley
%
\name{boxcox}
\alias{boxcox}
\alias{boxcox.default}
\alias{boxcox.formula}
\alias{boxcox.lm}
\title{
Box-Cox Transformations for Linear Models
}
\description{
Computes and optionally plots profile log-likelihoods for the
parameter of the Box-Cox power transformation.
}
\usage{
boxcox(object, \dots)
\method{boxcox}{default}(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp, eps = 1/50, xlab = expression(lambda),
ylab = "log-Likelihood", \dots)
\method{boxcox}{formula}(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp, eps = 1/50, xlab = expression(lambda),
ylab = "log-Likelihood", \dots)
\method{boxcox}{lm}(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp, eps = 1/50, xlab = expression(lambda),
ylab = "log-Likelihood", \dots)
}
\arguments{
\item{object}{a formula or fitted model object. Currently only \code{lm} and
\code{aov} objects are handled.}
\item{lambda}{vector of values of \code{lambda}
-- default \eqn{(-2, 2)} in steps of 0.1.}
\item{plotit}{logical which controls whether the result should be plotted.}
\item{interp}{logical which controls whether spline interpolation is
used. Default to \code{TRUE} if plotting with \code{lambda} of
length less than 100.}
\item{eps}{Tolerance for \code{lambda = 0}; defaults to 0.02.}
\item{xlab}{defaults to \code{"lambda"}.}
\item{ylab}{defaults to \code{"log-Likelihood"}.}
\item{\dots}{additional parameters to be used in the model fitting.}
}
\value{
A list of the \code{lambda} vector and the computed profile
log-likelihood vector, invisibly if the result is plotted.
}
\section{Side Effects}{
If \code{plotit = TRUE} plots loglik \emph{vs} \code{lambda} and
indicates a 95\% confidence interval about the maximum observed value
of \code{lambda}. If \code{interp = TRUE}, spline interpolation is
used to give a smoother plot.
}
\references{
Box, G. E. P. and Cox, D. R. (1964)
An analysis of transformations (with discussion).
\emph{Journal of the Royal Statistical Society B}, \bold{26}, 211--252.
Venables, W. N. and Ripley, B. D. (2002)
\emph{Modern Applied Statistics with S.} Fourth edition. Springer.
}
\examples{
data(trees)
boxcox(Volume ~ log(Height) + log(Girth), data = trees,
lambda = seq(-0.25, 0.25, length = 10))
boxcox(Days+1 ~ Eth*Sex*Age*Lrn, data = quine,
lambda = seq(-0.05, 0.45, len = 20))
}
\keyword{regression}
\keyword{models}
\keyword{hplot}
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