Testing bivariate independence based on <i>α</i>-divergence by improved probit transformation method for copula density estimation-Reference-Cited by-同舟云学术

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Testing bivariate independence based on α-divergence by improved probit transformation method for copula density estimation

Published:2022-01-12 Issue: Volume: Page:1-19
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Mohammadi M.¹²^ORCID,Emadi M.¹^ORCID,Amini M.³^ORCID

Affiliation:

1. Department of Statistics, Ferdowsi University of Mashhad, Mashhad, Iran

2. Department of Statistics, University of Zabol, Zabol, Iran

3. Department of Statistics, Ordered Data, Reliability and Dependency Center of Excellence, Ferdowsi University of Mashhad, Mashhad, Iran

Publisher

Informa UK Limited

Subject

Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2022.2025836

Reference33 articles.

1. A nonparametric estimation of the entropy for absolutely continuous distributions (Corresp.)

2. Testing independence based on Bernstein empirical copula and copula density

3. Distribution Free Tests of Independence Based on the Sample Distribution Function

4. Mutual information as a measure of multivariate association: analytical properties and statistical estimation

5. Charpentier, A., J. Fermanian, and O. Scaillet. 2006. Copulas: From theory to application in finance, chapter the estimation of copulas: Theory and Practice, vol. 1, 35–62. Torquay, UK: Risk Books.

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