#' Group Standard Deviations
#'
#' Calculates the standard deviations for each group
#'
#'
#' @param variables matrix or data frame with explanatory variables (may
#' contain missing values)
#' @param group vector or factor with group memberships
#' @param na.rm logical indicating whether missing values should be removed
#' @return matrix of group standard deviations (with variables in the rows, and
#' groups in the columns)
#' @author Gaston Sanchez
#' @seealso \code{\link{groupMeans}}, \code{\link{groupVars}},
#' \code{\link{groupMedians}}, \code{\link{groupQuants}}
#' @export
#' @examples
#'
#' \dontrun{
#' # dataset iris
#' data(iris)
#'
#' # group standard deviations
#' groupStds(iris[,1:4], iris[,5])
#' }
#'
groupStds <-
function(variables, group, na.rm=FALSE)
{
# Calculate std deviations by group
# variables: matrix or data frame with explanatory variables
# group: vector or factor with group memberships
# na.rm: logical indicating whether missing values should be removed
# check inputs
verify_Xy = my_verify(variables, group, na.rm=na.rm)
X = verify_Xy$X
y = verify_Xy$y
# how many groups
ng = nlevels(y)
# matrix with group std deviations
Stds = matrix(0, ncol(X), ng)
for (j in 1:ncol(X))
{
Stds[j,] = tapply(X[,j], y, FUN=sd, na.rm=na.rm)
}
# add names
if (is.null(colnames(X))) {
rownames(Stds) = paste("X", 1:ncol(X), sep="")
} else {
rownames(Stds) = colnames(X)
}
colnames(Stds) = levels(y)
# results
Stds
}
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