SampleGC: Gram-Charlier approximation to a multivariate density

In MultiStatM: Multivariate Statistical Methods

Gram-Charlier approximation to a multivariate density

Description

Provides the truncated Gram-Charlier approximation to a multivariate density. Approximation can be up to the first k=8 cumulants.

Usage

SampleGC(X, k = 4, cum = NULL)

Arguments

X	A matrix of d-variate data
k	the order of the approximation, by default set to 4; (k must not be smaller than 3 or greater than 8)
cum	if NULL (default) the cumulant vector is estimated from X. If cum is provided no estimation of cumulants is performed.

Value

The vector of the Gram-Charlier density evaluated at X

References

Gy.Terdik, Multivariate statistical methods - Going beyond the linear, Springer 2021. Section 4.7.

Examples

# Gram-Charlier density approximation (k=4) of data generated from
# a bivariate skew-gaussian distribution
n<-50
alpha<-c(10,0)
omega<-diag(2)
X<-rSkewNorm(n,omega,alpha)
EC<-SampleEVSK(X)
fy4<-SampleGC(X[1:5,],cum=EC)

MultiStatM documentation built on Sept. 11, 2024, 6:01 p.m.