Skip to contents

Compute kurtosis of a numeric vector

Source: R/FUNCTIONS_STATISTICAL.R
compute_kurtosis.Rd

Calculates the excess kurtosis of a numeric vector using the \(b_2\) formula consistent with MINITAB and BMDP. Missing values are removed before computation.

Usage

compute_kurtosis(vector)

Arguments

vector

Numeric vector.

Value

A numeric scalar. A value of 0 indicates a normal distribution; positive values indicate heavier tails (leptokurtic); negative values indicate lighter tails (platykurtic).

Note

Formula used: \(b_2 = m_4 / s^4 - 3 = (g_2 + 3)(1 - 1/n)^2 - 3\). Used in MINITAB and BMDP. Results match e1071::kurtosis() with type = 2.

Examples

set.seed(1)
vector <- rnorm(1000)
compute_kurtosis(vector)
#> [1] -0.007768915
e1071::kurtosis(vector)
#> [1] -0.007768915