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\name{rowMedians}
\alias{rowMedians}
\alias{rowMedians,matrix-method}
\alias{rowMedians,ExpressionSet-method}
\title{Calculates the median for each row in a matrix}
\description{
Calculates the median for each row in a matrix.
}
\usage{rowMedians(x, na.rm=FALSE, ...)}
\arguments{
\item{x}{A \code{\link[base]{numeric}} NxK \code{\link[base]{matrix}}.}
\item{na.rm}{If \code{\link[base:logical]{TRUE}},
\code{\link[base]{NA}}s are excluded first, otherwise not.}
\item{...}{Not use.}
}
\value{
Returns a \code{\link[base]{numeric}} \code{\link[base]{vector}} of
length N.
}
\section{Missing values}{
Missing values are excluded before calculating the medians.
}
\details{
The implementation of \code{rowMedians()}
is optimized for both speed and memory.
To avoid coercing to \code{\link[base]{double}}s (and hence memory
allocation), there is a special implementation for
\code{\link[base]{integer}} matrices. That is, if \code{x} is an
\code{\link[base]{integer}} \code{\link[base]{matrix}}, then
\code{rowMedians(as.double(x))} would require three times the memory
of \code{rowMedians(x)}, but all this is avoided.
}
\author{Henrik Bengtsson}
\seealso{
See \code{rowMeans()} in \code{\link[base]{colSums}}().
}
\examples{
set.seed(1)
x <- rnorm(n=234*543)
x[sample(1:length(x), size=0.1*length(x))] <- NA
dim(x) <- c(234,543)
y1 <- rowMedians(x, na.rm=TRUE)
y2 <- apply(x, MARGIN=1, FUN=median, na.rm=TRUE)
stopifnot(all.equal(y1, y2))
x <- cbind(x1=3, x2=c(4:1, 2:5))
stopifnot(all.equal(rowMeans(x), rowMedians(x)))
}
\keyword{manip}
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