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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/methods.R, R/methods_row.R
\name{colVars,xgCMatrix-method}
\alias{colVars,xgCMatrix-method}
\alias{rowVars,xgCMatrix-method}
\title{Calculates the variance for each row (column) of a matrix-like object}
\usage{
\S4method{colVars}{xgCMatrix}(
x,
rows = NULL,
cols = NULL,
na.rm = FALSE,
center = NULL,
useNames = TRUE
)
\S4method{rowVars}{xgCMatrix}(
x,
rows = NULL,
cols = NULL,
na.rm = FALSE,
center = NULL,
useNames = TRUE
)
}
\arguments{
\item{x}{An NxK matrix-like object.}
\item{rows, cols}{A \code{\link{vector}} indicating the subset of rows
(and/or columns) to operate over. If \code{\link{NULL}}, no subsetting is
done.}
\item{na.rm}{If \code{\link[base]{TRUE}}, missing values
(\code{\link[base]{NA}} or \code{\link[base]{NaN}}) are
omitted from the calculations.}
\item{center}{(optional) the center, defaults to the row means.}
\item{useNames}{If \code{\link{TRUE}} (default), names attributes of result are set. Else if \code{\link{FALSE}}, no naming support is done.}
}
\value{
Returns a \code{\link{numeric}} \code{\link{vector}} of length N (K).
}
\description{
Calculates the variance for each row (column) of a matrix-like object.
}
\details{
The S4 methods for \code{x} of type \code{\link{matrix}},
\code{\link{array}}, \code{\link{table}}, or \code{\link{numeric}} call
\code{matrixStats::\link[matrixStats]{rowVars}} /
\code{matrixStats::\link[matrixStats]{colVars}}.
}
\examples{
mat <- matrix(rnorm(15), nrow = 5, ncol = 3)
mat[2, 1] <- NA
mat[3, 3] <- Inf
mat[4, 1] <- 0
print(mat)
rowVars(mat)
colVars(mat)
}
\seealso{
\itemize{
\item \code{matrixStats::\link[matrixStats]{rowVars}()} and
\code{matrixStats::\link[matrixStats:rowVars]{colVars}()} which are used
when the input is a \code{matrix} or \code{numeric} vector.
\item For mean estimates, see \code{\link[MatrixGenerics]{rowMeans2}()} and
\code{\link[base:colSums]{rowMeans}()}.
\item For standard deviation estimates, see \code{\link[MatrixGenerics]{rowSds}()}.
\item \code{stats::\link[stats:cor]{var}()}.
}
}
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