AMR/R/kurtosis.R

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# ==================================================================== #
# TITLE: #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
# #
# SOURCE CODE: #
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# https://github.com/msberends/AMR #
# #
# PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, et al. (2022). #
# AMR: An R Package for Working with Antimicrobial Resistance Data. #
# Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
# #
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# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
#' Kurtosis of the Sample
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#'
#' @description Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. A normal distribution has a kurtosis of 3 and a excess kurtosis of 0.
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#' @param x a vector of values, a [matrix] or a [data.frame]
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#' @param na.rm a [logical] to indicate whether `NA` values should be stripped before the computation proceeds
#' @param excess a [logical] to indicate whether the *excess kurtosis* should be returned, defined as the kurtosis minus 3.
#' @seealso [skewness()]
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#' @rdname kurtosis
#' @export
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#' @examples
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#' kurtosis(rnorm(10000))
#' kurtosis(rnorm(10000), excess = TRUE)
kurtosis <- function(x, na.rm = FALSE, excess = FALSE) {
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
meet_criteria(excess, allow_class = "logical", has_length = 1)
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UseMethod("kurtosis")
}
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#' @method kurtosis default
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#' @rdname kurtosis
#' @export
kurtosis.default <- function(x, na.rm = FALSE, excess = FALSE) {
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
meet_criteria(excess, allow_class = "logical", has_length = 1)
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x <- as.vector(x)
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if (isTRUE(na.rm)) {
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x <- x[!is.na(x)]
}
n <- length(x)
k <- n * sum((x - mean(x, na.rm = na.rm))^4, na.rm = na.rm) /
(sum((x - mean(x, na.rm = na.rm))^2, na.rm = na.rm)^2)
k - ifelse(excess, 3, 0)
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}
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#' @method kurtosis matrix
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#' @rdname kurtosis
#' @export
kurtosis.matrix <- function(x, na.rm = FALSE, excess = FALSE) {
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
meet_criteria(excess, allow_class = "logical", has_length = 1)
apply(x, 2, kurtosis.default, na.rm = na.rm, excess = excess)
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}
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#' @method kurtosis data.frame
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#' @rdname kurtosis
#' @export
kurtosis.data.frame <- function(x, na.rm = FALSE, excess = FALSE) {
meet_criteria(na.rm, allow_class = "logical", has_length = 1)
meet_criteria(excess, allow_class = "logical", has_length = 1)
vapply(FUN.VALUE = double(1), x, kurtosis.default, na.rm = na.rm, excess = excess)
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}