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\name{anova.lmRob}
\alias{anova.lmRob}
\alias{anova.lmRoblist}
\title{ANOVA for Robust Linear Model Fits}
\description{
Compute an analysis of variance table for one or more robust linear model fits.
}
\usage{
\method{anova}{lmRob}(object, ..., test = c("RF", "RWald"))
\method{anova}{lmRoblist}(object, const, ipsi, yc, test = c("RWald", "RF"), ...)
}
\arguments{
\item{object}{an lmRob object.}
\item{\dots}{additional arguments required by the generic anova function. If \code{\dots} contains additional robustly fitted linear models then the function \code{\link{anova.lmRoblist}} is dispatched.}
\item{const}{a numeric value containing the tuning constant.}
\item{ipsi}{an integer value specifying the psi-function.}
\item{yc}{a numeric value containing the tuning constant.}
\item{test}{a single character value specifying which test should be computed in the Anova table. The possible choices are "RWald" and "RF".}
}
\details{
The default test used by anova is the \code{"RWald"} test, which is the Wald test based on robust estimates of the coefficients and covariance matrix. If \code{test} is \code{"RF"}, the robustified F-test is used instead.
}
\value{
an \code{anova} object.
}
\section{References}{
Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., and Stahel, W. A. (1986). \emph{Robust statistics: the approach based on influence functions}. John Wiley & Sons.
}
\seealso{
\code{\link{lmRob}},
\code{\link{anova}}.
}
\examples{
data(stack.dat)
stack.small <- lmRob(Loss ~ Water.Temp + Acid.Conc., data = stack.dat)
stack.full <- lmRob(Loss ~ ., data = stack.dat)
anova(stack.full)
anova(stack.full, stack.small)
}
\keyword{robust}
\keyword{regression}
\keyword{methods}
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