Testing independence for Archimedean copula based on Bernstein estimate of Kendall distribution function

Susam S. O., Hüdaverdi B.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.88, no.13, pp.2589-2599, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 88 Issue: 13
  • Publication Date: 2018
  • Doi Number: 10.1080/00949655.2018.1478978
  • Journal Name: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2589-2599
  • Keywords: Kendall distribution function, Bernstein polynomial, Cramer-von-Mises statistic, independence test, DENSITY
  • Dokuz Eylül University Affiliated: Yes

Abstract

In this study, we estimate the Kendall distribution function (K(t)) for Archimedean copula family using Bernstein polynomial approximation and we investigate its performance by Monte Carlo simulation. Then, we introduce a nonparametric test of independence which is based on Cramer-von-Mises distance of the new estimate of Kendall distribution function. Also, we examine the power and the size of the test and we compare it with the classical nonparametric test that is based on the empirical Kendall distribution function.