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

DOI10.1080/00949655.2018.1478978OpenAlexW2806124024MaRDI QIDQ4960707

Burcu Hudaverdi Ucer, Selim Orhun Susam

Publication date: 23 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2018.1478978

zbMATH Keywords

Bernstein polynomialindependence testKendall distribution functionCramér-von-Mises statistic

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (8)

A consistent statistical test based on bivariate random samples ⋮ A multi-parameter Generalized Farlie-Gumbel-Morgenstern bivariate copula family via Bernstein polynomial ⋮ Unnamed Item ⋮ A goodness-of-fit test based on Bézier curve estimation of Kendall distribution ⋮ A weighted independence test based on smooth estimation of Kendall distribution ⋮ On the weighted tests of independence based on Bernstein empirical copula ⋮ Unnamed Item ⋮ Asymptotic properties of Bernstein estimators on the simplex

Cites Work

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• On the simultaneous associativity of F(x,y) and x+y-F(x,y)
• An introduction to copulas. Properties and applications
• Application of Bernstein polynomials for smooth estimation of a distribution and density function
• On estimating distribution functions using Bernstein polynomials
• Statistical Inference Procedures for Bivariate Archimedean Copulas
• Goodness-of-fit Procedures for Copula Models Based on the Probability Integral Transformation
• Distribution function estimation by constrained polynomial spline regression
• Chung–Smirnov property for Bernstein estimators of distribution functions
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• Testing independence based on Bernstein empirical copula and copula density
• Distribution Free Tests of Independence Based on the Sample Distribution Function

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