Dependence structure and test of independence for some well-known bivariate distributions

DOI10.1007/S00180-016-0696-9zbMath1417.62132OpenAlexW2533512789MaRDI QIDQ1695423

Peng Zhang

Publication date: 7 February 2018

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-016-0696-9

zbMATH Keywords

U-statisticscopula functionsnegative quadrant dependenceCelebioğlu-Cuadras copulaGumbel-Barnett distributionGumbel's bivariate distribution

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (1)

New non-parametric tests for independence

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• An introduction to copulas.
• Constructing copula functions with weighted geometric means
• Distribution-free tests for independence against positive quadrant dependence: a generaliza\-tion
• Aspects of Dependence in Generalized Farlie-Gumbel-Morgenstern Distributions
• Approximation Theorems of Mathematical Statistics
• DISTRIBUTION‐FREE TESTS BASED ON SUB‐SAMPLE EXTREMA FOR TESTING AGAINST POSITIVE DEPENDENCE
• Local dependence functions for extreme value distributions
• Competitors of the Kendall-tau test for testing independence against positive quadrant dependence
• Frank's family of bivariate distributions
• A Continuous Bivariate Exponential Extension
• Some Concepts of Dependence

This page was built for publication: Dependence structure and test of independence for some well-known bivariate distributions