Becker, NielsUtev, Sergey2015-12-130047-259Xhttp://hdl.handle.net/1885/91734A 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.Keywords: Characterizing discrete distributions; Charaterizing independence; Conditional specification; Identifiability of mixtures; Multivariate discrete distributions; Regression function200210.1006/jmva.2001.20612015-12-12