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41 lines
1.4 KiB
R
41 lines
1.4 KiB
R
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#' Skewness of the sample
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#'
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#' @description Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
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#'
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#' When negative: the left tail is longer; the mass of the distribution is concentrated on the right of the figure. When positive: the right tail is longer; the mass of the distribution is concentrated on the left of the figure.
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#' @param x a vector of values, a \code{matrix} or a \code{data frame}
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#' @param na.rm a logical value indicating whether \code{NA} values should be stripped before the computation proceeds.
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#' @exportMethod skewness
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#' @seealso \code{\link{kurtosis}}
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#' @rdname skewness
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#' @export
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skewness <- function(x, na.rm = FALSE) {
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UseMethod("skewness")
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}
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#' @exportMethod skewness.default
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#' @rdname skewness
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#' @export
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skewness.default <- function (x, na.rm = FALSE) {
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x <- as.vector(x)
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if (na.rm == TRUE) {
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x <- x[!is.na(x)]
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}
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n <- length(x)
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(base::sum((x - base::mean(x))^3) / n) / (base::sum((x - base::mean(x))^2) / n)^(3/2)
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}
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#' @exportMethod skewness.matrix
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#' @rdname skewness
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#' @export
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skewness.matrix <- function (x, na.rm = FALSE) {
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base::apply(x, 2, skewness.default, na.rm = na.rm)
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}
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#' @exportMethod skewness.data.frame
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#' @rdname skewness
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#' @export
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skewness.data.frame <- function (x, na.rm = FALSE) {
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base::sapply(x, skewness.default, na.rm = na.rm)
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}
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