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\name{lmRob.fit}
\alias{lmRob.fit}
\alias{lmRob.wfit}
\title{Robust Fitter Functions for Linear Models}
\description{
These are the basic computing engines called by \code{lmRob} used to robustly fit linear models. These functions are not intended to be used directly.
}
\usage{
lmRob.fit(x, y, x1.idx = NULL, nrep = NULL, robust.control = NULL, ...)
lmRob.wfit(x, y, w, x1.idx = NULL, nrep = NULL, robust.control = NULL, ...)
}
\arguments{
\item{x}{a numeric matrix containing the design matrix.}
\item{y}{a numeric vector containing the linear model response.}
\item{w}{a numeric vector containing the weights.}
\item{x1.idx}{a numeric vector containing the indices of columns of the design matrix arising from the coding of factor variables.}
\item{nrep}{the number of random subsamples to be drawn. If \code{"Exhaustive"} resampling is being used, the value of \code{nrep} is ignored.}
\item{robust.control}{a list of control parameters to be used in the numerical algorithms. See \code{lmRob.control} for the possible control parameters and their default settings.}
\item{\dots}{additional arguments.}
}
\keyword{robust}
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