SampleSkew {MultiStatM} | R Documentation |
Estimation of Sample Skewness (Mardia, MRSz)
Description
Estimates the sample skewness index based on the specified method: Mardia or MRSz.
Usage
SampleSkew(x, Type = c("Mardia", "MRSz"))
Arguments
x |
A matrix of multivariate data. |
Type |
A character string specifying the type of skewness index to estimate. Use "Mardia" for Mardia's skewness index or "MRSz" for the Mori-Rohatgi-Szekely skewness vector and index. |
Value
A list containing the estimated skewness index or vector and the associated p-value under the Gaussian hypothesis.
Mardia.Skewness |
The skewness index when |
MRSz.Skewness.Vector |
The skewness vector when |
MRSz.Skewness.Index |
The skewness index when |
p.value |
The p-value under the Gaussian hypothesis for the estimated skewness. |
References
Gy.Terdik, Multivariate statistical methods - going beyond the linear, Springer 2021. Example 6.1 and 6.2.
S. R. Jammalamadaka, E. Taufer, Gy. Terdik. On multivariate skewness and kurtosis. Sankhya A, 83(2), 607-644.
See Also
Other Estimation:
SampleEVSK()
,
SampleKurt()
,
SampleMomCum()
,
VarianceKurt()
,
VarianceSkew()
Examples
# Mardia's skewness example
x <- matrix(rnorm(100*5), ncol=5)
SampleSkew(x, Type = "Mardia")
# MRSz's skewness example
SampleSkew(x, Type = "MRSz")