Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 509-524 |
| Number of pages | 16 |
| Journal | Journal of Multivariate Analysis |
| Volume | 83 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Nov 2002 |
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