Estimation and goodness-of-fit procedures for Farlie-Gumbel-Morgenstern bivariate copula of order statistics

HÜDAVERDİ B., OzkalYildiz T.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol.82, no.1, pp.137-147, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 82 Issue: 1
  • Publication Date: 2012
  • Doi Number: 10.1080/00949655.2010.530602
  • Journal Name: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.137-147
  • Keywords: Farlie-Gumbel-Morgenstern copula, order statistics, maximum pseudo-likelihood estimation, goodness-of-fit tests, bootstrap, DEPENDENCE, INFERENCE
  • Dokuz Eylül University Affiliated: Yes

Abstract

In this study, we provide the Farlie-Gumbel-Morgenstern bivariate copula of rth and sth order statistics. The main emphasis in this study is on the inference procedure which is based on the maximum pseudo-likelihood estimate for the copula parameter. As for the methodology, goodness-of-fit test statistic for copulas which is based on a Cramer-von Mises functional of the empirical copula process is applied for selecting an appropriate model by bootstrapping. An application of the methodology to simulated data set is also presented.