kurtosis: Excess kurtosis (Copied from the deprecated R-package modes)

In BenjaminPlanterose/UMtools: An R-package for analysing Illumina DNA Methylation arrays at the fluorescence intensity level

Excess kurtosis (Copied from the deprecated R-package modes)

Description

Computes excess kurtosis.

Usage

kurtosis(x, finite)

Arguments

x	Data vector.
finite	Should the finite sample correction (bias correction) be used? Defaults to TRUE.

Details

Due to discontinuation from CRAN (Package ‘modes’ was removed from the CRAN repository; Archived on 2020-03-03 as check problems were not corrected despite reminders), we have copied the required functions into UMtools to ease installation (and slightly modified). The original documentation states the following: "This function calculates the excess kurtosis of a data vector with optional bias correction. Kurtosis is a meaure of the peakedness or how heavy the tails of a distribution are–this dual interpretation is a result of the obvious inverse relationship between fat tails and high peaks. Excess kurtosis is simply "kurtosis-3." This is a correction that is often done to allow for comparision to the normal distribution–which has a kurtosis of 3 and excess kurtosis of 0. A kurtosis greater than 0 means that the distribution is leptokurtic and so has a high peak with skinny tails. Conversely, a kurtosis less than 0 means that the distribution is platykurtic and so has a low peak and heavy tails. This interpretation is slightly more complicated once the distribution is not unimodal and/or non-zero skewness. Comparing to Gaussian (normal) moments is more acceptable in these cases".

Value

Kurtosis (numeric)

Examples

data <- c(rnorm(15, 0, 1), rnorm(21, 5, 1))
hist(data)
kurtosis(data, TRUE)

BenjaminPlanterose/UMtools documentation built on Aug. 19, 2024, 4:54 a.m.