\HeaderA{pamr.plotcv}{A function to plot the cross-validated  error curves from
the nearest shrunken centroid
classifier}{pamr.plotcv}
\begin{Description}\relax
A function to plot the cross-validated error curves
the nearest shrunken centroid
classifier
\end{Description}
\begin{Usage}
\begin{verbatim}
pamr.plotcv(fit)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{fit}] The result of a call to pamr.cv
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
\code{pamr.plotcv} plots the cross-validated misclassification error
curves,   from nearest shrunken
centroid classifier. An overall plot, and a plot by class, are produced.
\end{Details}
\begin{Value}
\end{Value}
\begin{Author}\relax
Trevor Hastie,Robert Tibshirani, Balasubramanian Narasimhan, and Gilbert Chu
\end{Author}
\begin{References}\relax
\end{References}
\begin{Examples}
\begin{ExampleCode}
set.seed(120)
x <- matrix(rnorm(1000*20),ncol=20)
y <- sample(c(1:4),size=20,replace=TRUE)
mydata <- list(x=x,y=y)
mytrain <-   pamr.train(mydata)
mycv <-  pamr.cv(mytrain, mydata)
pamr.plotcv(mycv)
\end{ExampleCode}
\end{Examples}

