Title

Dependence Structure of some Bivariate Distributions

Document Type

Article

Publication Date

1-1-2014

Publication Title

Serdica Journal of Computing

Abstract

Dependence in the world of uncertainty is a complex concept. However, it exists, is asymmetric, has magnitude and direction, and can be measured. We use some measures of dependence between random events to illustrate how to apply it in the study of dependence between non-numeric bivariate variables and numeric random variables. Graphics show what is the inner dependence structure in the Clayton Archimedean copula and the Bivariate Poisson distribution. We know this approach is valid for studying the local dependence structure for any pair of random variables determined by its empirical or theoretical distribution. And it can be used also to simulate dependent events and dependent r/v/’s, but some restrictions apply.

Volume

8

Issue

3

First Page

233

Last Page

254

ISSN

1312-6555

Rights

© 2014 Institute of Mathematics and Informatics Bulgarian Academy of Sciences

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