\HeaderA{normalize.loess}{Normalized chips using cyclic loess.}{normalize.loess}
\keyword{documentation}{normalize.loess}
\keyword{utilities}{normalize.loess}
\begin{Description}\relax
Takes a matrix and apply cyclic loess normalization. It is based in
normalize.loess from package affy but supports NA.
\end{Description}
\begin{Usage}
\begin{verbatim}
  normalize.loess(mat, subset = sample(1:(dim(mat)[1]), 
    min(c(5000, nrow(mat)))), epsilon = 10^-2, maxit = 1, log.it = TRUE,
        verbose = FALSE, span = 2/3, family.loess = "symmetric", weights = NULL)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{mat}] a matrix with columns containing the values of the chips
to normalize.
\item[\code{subset}] a subset of the data to fit a loess to.
\item[\code{epsilon}] a tolerance value (supposed to be a small value - used
as a stopping criterium).
\item[\code{maxit}] maximum number of iterations.
\item[\code{log.it}] logical. If \code{TRUE} it takes the log2 of \code{mat}
\item[\code{verbose}] logical. If \code{TRUE} displays current pair of chip being
worked on.
\item[\code{span}] parameter to be passed the function \code{\LinkA{loess}{loess}}
\item[\code{family.loess}] parameter to be passed the function
\code{\LinkA{loess}{loess}}. \code{"gaussian"} or \code{"symmetric"}
are acceptable values for this parameter.
\item[\code{weights}] a vector of weights for the individual measurements.
\end{ldescription}
\end{Arguments}
\begin{Value}
A matrix of normalized values.
\end{Value}
\begin{Author}\relax
Diego Diez
\end{Author}
\begin{Examples}
\begin{ExampleCode}
## Not run: 
        mat <- matrix(sample(500), 100, 5)
        mat <- normalize.loess(mat)
## End(Not run)
\end{ExampleCode}
\end{Examples}

