kurt: Kurtosis

In jeksterslabds/jeksterslabRdist: Jekster's Lab Distribution Utilities

Description

Calculates kurtosis which is a measure of the "taildness" of a distribution.

Usage

kurt(x, type = 2, excess = TRUE)

Arguments

x	Numeric vector. Sample data.
type	Integer. 1, 2, or 3. See details.
excess	Logical. Return excess kurtosis (kurtosis minus 3).

Details

Type 1

g_2 = \frac{m_4}{m_{2}^{2}} %(\#eq:dist-moments-g2)

Type 2

G_2 = \frac{K_4}{K_{2}^{2}} %(\#eq:dist-moments-G2)

Type 3

b_2 = \frac{m_4}{s^4} %(\#eq:dist-moments-b2)

Author(s)

Ivan Jacob Agaloos Pesigan

References

Joanes, D., & Gill, C. (1998). Comparing Measures of Sample Skewness and Kurtosis. Journal of the Royal Statistical Society. Series D (The Statistician), 47(1), 183-189. 2988433

Wikipedia: Kurtosis

See Also

Other moments functions: cumulant(), moments(), moment(), skew()

Examples

x <- c(
  10, 11, 12, 12, 12, 13, 13, 13, 13, 13,
  13, 14, 14, 14, 14, 15, 15, 15, 16, 17
)
kurt(x, type = 1)
kurt(x, type = 2)
kurt(x, type = 3)
x <- rnorm(n = 1000)
kurt(x, type = 1)
kurt(x, type = 2)
kurt(x, type = 3)

jeksterslabds/jeksterslabRdist documentation built on Aug. 9, 2020, 7:33 a.m.