pncs: Cdf for non-central squared copula

In CopulaInference: Estimation and Goodness-of-Fit of Copula-Based Models with Arbitrary Distributions

Cdf for non-central squared copula

Description

This function computes the distribution function of the non-central squared copula (ncs) associated a with one-parameter copula with parameter cpar, and parameters a1, a2 >0 .

Usage

pncs(data, family, rotation = 0, par)

Arguments

data	Matrix (x,y) of size n x 2
family	Copula family: "ncs-gaussian", "ncs-clayton", "ncs-frank", "ncs-gumbel", "ncs-joe", "ncs-plackett”.
rotation	Rotation: 0 (default value), 90, 180, or 270.
par	vector of copula parameter and non-centrality parameter a1,a2 >0

Value

cdf	Value of cdf

References

Nasri (2020). On non-central squared copulas. Statistics and Probability Letters.

Examples

pncs(c(0.5,0.8),"ncs-clayton", par=c(2,1,2),rotation=270)

CopulaInference documentation built on April 21, 2023, 9:07 a.m.