bootstrapfun: Function to perform parametric bootstrap for goodness-of-fit...

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

Function to perform parametric bootstrap for goodness-of-fit tests

Description

This function simulates Cramer-von Mises statistic and Kendall's statistic using parametric bootstrap for arbitrary data.

Usage

bootstrapfun(object)

Arguments

object

object of class 'statcvm'.

Value

Sn	Simulated value of the Cramer-von Mises statistic
Tn	simulated value of the Kendall's statistic
Rn	simulated value of the Spearman's statistic
parB	Estimated parameter

References

Nasri & Remillard (2023). Identifiability and inference for copula-based semiparametric models for random vectors with arbitrary marginal distributions. arXiv 2301.13408.

Nasri & Remillard (2023). Goodness-of-fit and bootstrapping for copula-based random vectors with arbitrary marginal distributions.

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