moments: Skewness and (excess) Kurtosis of a vector of values

In propagate: Propagation of Uncertainty

Skewness and (excess) Kurtosis of a vector of values

Description

These functions calculate skewness and excess kurtosis of a vector of values. They were taken from the package 'moments'.

Usage

skewness(x, na.rm = FALSE) 
kurtosis(x, na.rm = FALSE) 

Arguments

x	a numeric vector, matrix or data frame.
na.rm	logical. Should missing values be removed?

Details

Skewness:

\frac{\frac{1}{n} \sum_{i=1}^n (x_i-\overline{x})^3}{\left(\frac{1}{n} \sum_{i=1}^n (x_i-\overline{x})^2\right)^{3/2}}

(excess) Kurtosis:

\frac{\frac{1}{n} \sum_{i=1}^n (x_i - \overline{x})^4}{\left(\frac{1}{n} \sum_{i=1}^n (x_i - \overline{x})^2\right)^2} - 3

Value

The skewness/kurtosis values.

Author(s)

Andrej-Nikolai Spiess

Examples

X <- rnorm(100, 20, 2)
skewness(X)
kurtosis(X)

propagate documentation built on June 8, 2025, 9:59 a.m.