Test of Independence for Baker’s Bivariate Distributions
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Publication:2828695
DOI10.1080/03610918.2014.917676zbMath1348.62181OpenAlexW2317869058MaRDI QIDQ2828695
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Publication date: 26 October 2016
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2014.917676
Nonparametric tolerance and confidence regions (62G15) Order statistics; empirical distribution functions (62G30)
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Cites Work
- Dependence structures and asymptotic properties of Baker's distributions with fixed marginals
- From the Huang-Kotz FGM distribution to Baker's bivariate distribution
- Dependence structure and symmetry of Huang-Kotz FGM distributions and their extensions
- An order-statistics-based method for constructing multivariate distributions with fixed margin\-als
- A note on the maximum correlation for Baker's bivariate distributions with fixed marginals
- Dependence structure of bivariate order statistics with applications to Bayramoglu's distribu\-tions
- Test of independence for generalized Farlie-Gumbel-Morgenstern distributions
- Aspects of Dependence in Generalized Farlie-Gumbel-Morgenstern Distributions
- The performance of some correlation coefficients for a general bivariate distribution
- Competitors of the Kendall-tau test for testing independence against positive quadrant dependence
- Correlation structure in Farlie-Gumbel-Morgenstern distributions
- Test of Independence in the Farlie–Gumbel–Morgenstern Distribution
- Elements of Information Theory
- Some Concepts of Dependence
- Modifications of the Farlie-Gumbel-Morgenstern distributions. A tough hill to climb.
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