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\name{RegBest}
\alias{RegBest}
\title{Select variables in multiple linear regression}
\description{
Find an optimal submodel
}
\usage{
RegBest(y,x, int = TRUE, wt=NULL, na.action = na.omit,
method=c("r2","Cp", "adjr2"), nbest=1)
}
\arguments{
\item{y}{A response vector}
\item{x}{A matrix of predictors}
\item{int}{Add an intercept to the model}
\item{wt}{Optional weight vector}
\item{na.action}{Handling missing values}
\item{method}{Calculate R-squared, adjusted R-squared or Cp to select the model. By default a the F-test on the r-square is used}
\item{nbest}{number of best models for each set of explained variables (by default 1)}
}
\value{
Returns the objects
\item{all}{gives all the \code{nbest} best models for a given number of variables}
\item{best}{the best model}
}
\author{Francois Husson \email{francois.husson@institut-agro.fr}}
\seealso{ \code{\link{lm}}}
\examples{
data(milk)
res = RegBest(y=milk[,6],x=milk[,-6])
res$best
}
\keyword{models}
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