Multivariate Discrete Distributions with a Product-Type Dependence
A discrete multivariate probability distribution for dependent random variables, which contains the Poisson and Geometric conditionals distributions as particular cases, is characterized by means of conditional expectations of arbitrary one-to-one functions. Independence of the random variables is also characterized in terms of these conditional expectations. For certain exchangeable and partially exchangeable random variables with a joint distribution of this form it is shown that maximum likelihood estimates coincide with the simple method of moments estimates, suggesting that these models offer a pragmatic way to analyze certain dependent data.
Year of publication: |
2002
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Authors: | Becker, Niels G. ; Utev, Sergey |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 83.2002, 2, p. 509-524
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Publisher: |
Elsevier |
Keywords: | characterizing discrete distributions characterizing independence conditional specification identifiability of mixtures multivariate discrete distributions regression function |
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