hncs: Conditional distribution of non-central squared copula

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

Conditional distribution of non-central squared copula

Description

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

Usage

hncs(data, cond_var, family, rotation = 0, par)

Arguments

data	Matrix (x,y) of size n x 2
cond_var	Conditioning variable (1 or 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

h	Conditional cdf

References

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

Examples

hncs(c(0.5,0.8),1,"ncs-clayton",270,c(2,1,2))

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