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

Susam S. O., Hüdaverdi B.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, cilt.88, sa.13, ss.2589-2599, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 88 Sayı: 13
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1080/00949655.2018.1478978
  • Dergi Adı: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2589-2599
  • Anahtar Kelimeler: Kendall distribution function, Bernstein polynomial, Cramer-von-Mises statistic, independence test, DENSITY
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

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.