EVSKSkewNorm

Computes the theoretical values of the mean vector, covariance, skewness vector,
total skenwness, kurtosis vector and total
kurtosis for the multivariate Skew Normal distribution

Algorithms to build set partitions and commutator matrices and their use in the
construction of multivariate d-Hermite polynomials;  estimation and derivation of theoretical  vector moments and vector
cumulants  of multivariate distributions; conversion formulae for multivariate moments and cumulants. Applications to
estimation and derivation of multivariate measures of skewness and kurtosis;  estimation and derivation of asymptotic
covariances for d-variate Hermite polynomials, multivariate moments and cumulants and measures of skewness and kurtosis.
The formulae implemented are discussed in Terdik (2021, ISBN:9783030813925), "Multivariate Statistical Methods".

Emanuele Taufer

MultiStatM

Multivariate Statistical Methods

Gyorgy Terdik

EVSKSkewNorm function

<dl><dt>omega</dt>
<dd>A \(d \times d\) correlation matrix</dd>
<dt>alpha</dt>
<dd>shape parameter d-vector</dd></dl>

Arguments

EVSK multivariate Skew Normal — EVSKSkewNorm

<dl>

<dt>omega</dt>
<dd>A \(d \times d\) correlation matrix</dd>


<dt>alpha</dt>
<dd>shape parameter d-vector</dd>

</dl>

EVSKSkewNorm: EVSK multivariate Skew Normal

Description

Usage

Value

Arguments

References

See Also

Examples