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#' Group Quantiles
#'
#' Calculates the specified quantiles 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 prob probability value (numeric value between 0 and 1)
#' @param na.rm logical indicating whether missing values should be removed
#' @return matrix of group quantiles (with variables in the rows, and groups in
#' the columns)
#' @author Gaston Sanchez
#' @seealso \code{\link{groupMeans}}, \code{\link{groupVars}},
#' \code{\link{groupStds}}, \code{\link{groupMedians}}
#' @export
#' @examples
#'
#' \dontrun{
#' # dataset iris
#' data(iris)
#'
#' # group quantile prob=20
#' groupQuants(iris[,1:4], iris[,5], prob=0.20)
#' }
#'
groupQuants <-
function(variables, group, prob, na.rm=FALSE)
{
# Calculate quantile deviations by group
# variables: matrix or data frame with explanatory variables
# group: vector or factor with group memberships
# prob: probability value in [0,1]
# 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
# quantile
if (missing(prob)) {
stop("\nOoops, argument 'prob' is missing")
} else {
if (length(prob) > 1)
stop("\nOoops, 'prob' has length > 1")
if (prob < 0 || prob > 1)
stop("\nOoops, invalid 'prob' value")
}
# how many groups
ng = nlevels(y)
# matrix with group quantiles
Quants = matrix(0, ncol(X), ng)
for (j in 1:ncol(X))
{
Quants[j,] = tapply(X[,j], y, FUN=quantile, probs=prob, na.rm=na.rm)
}
# add names
if (is.null(colnames(X))) {
rownames(Quants) = paste("X", 1:ncol(X), sep="")
} else {
rownames(Quants) = colnames(X)
}
colnames(Quants) = levels(y)
# results
Quants
}
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