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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/BoxCoxTrans.R
\name{BoxCoxTrans}
\alias{BoxCoxTrans}
\alias{BoxCoxTrans.default}
\alias{predict.BoxCoxTrans}
\alias{expoTrans.default}
\alias{expoTrans}
\alias{predict.expoTrans}
\alias{print.BoxCoxTrans}
\title{Box-Cox and Exponential Transformations}
\usage{
BoxCoxTrans(y, ...)
\method{BoxCoxTrans}{default}(
y,
x = rep(1, length(y)),
fudge = 0.2,
numUnique = 3,
na.rm = FALSE,
...
)
\method{print}{BoxCoxTrans}(x, newdata, digits = 3, ...)
\method{predict}{BoxCoxTrans}(object, newdata, ...)
}
\arguments{
\item{y}{a numeric vector of data to be transformed. For \code{BoxCoxTrans}, the data must be strictly positive.}
\item{\dots}{for \code{BoxCoxTrans}: options to pass to \code{\link[MASS]{boxcox}}. \code{plotit} should not be passed through. For \code{predict.BoxCoxTrans}, additional arguments are ignored.}
\item{x}{an optional dependent variable to be used in a linear model.}
\item{fudge}{a tolerance value: lambda values within +/-fudge will be coerced to 0 and within 1+/-fudge will be coerced to 1.}
\item{numUnique}{how many unique values should \code{y} have to estimate the transformation?}
\item{na.rm}{a logical value indicating whether \code{NA} values should be stripped from \code{y} and \code{x} before the computation proceeds.}
\item{newdata}{a numeric vector of values to transform.}
\item{digits}{minimal number of \emph{significant digits}.}
\item{object}{an object of class \code{BoxCoxTrans} or \code{expoTrans}.}
}
\value{
Both functions returns a list of class of either \code{BoxCoxTrans} or \code{expoTrans} with
elements
\item{lambda }{estimated transformation value}
\item{fudge }{value of \code{fudge}}
\item{n }{number of data points used to estimate lambda}
\item{summary }{the results of \code{summary(y)}}
\item{ratio }{\code{max(y)/min(y)}}
\item{skewness }{sample skewness statistic}
\code{BoxCoxTrans} also returns: \item{fudge }{value of \code{fudge}}
The \code{predict} functions returns numeric vectors of transformed values
}
\description{
These classes can be used to estimate transformations and apply them to existing and future data
}
\details{
\code{BoxCoxTrans} function is basically a wrapper for the \code{\link[MASS]{boxcox}} function in the MASS library. It can be used to estimate the transformation and apply it to new data.
\code{expoTrans} estimates the exponential transformation of Manly (1976) but assumes a common mean for
the data. The transformation parameter is estimated by directly maximizing the likelihood.
If \code{any(y <= 0)} or if \code{length(unique(y)) < numUnique}, lambda is not estimated and no
transformation is applied.
}
\examples{
data(BloodBrain)
ratio <- exp(logBBB)
bc <- BoxCoxTrans(ratio)
bc
predict(bc, ratio[1:5])
ratio[5] <- NA
bc2 <- BoxCoxTrans(ratio, bbbDescr$tpsa, na.rm = TRUE)
bc2
manly <- expoTrans(ratio)
manly
}
\references{
Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations (with discussion). Journal of the Royal Statistical Society B, 26, 211-252.
Manly, B. L. (1976) Exponential data transformations. The Statistician, 25, 37 - 42.
}
\seealso{
\code{\link[MASS]{boxcox}}, \code{\link{preProcess}}, \code{\link{optim}}
}
\author{
Max Author
}
\keyword{utilities}
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