Identifiability of Modified Power Series Mixtures via Posterior Means

Arjun K. Gupta, Truc T. Nguyen, Yinning Wang and Jacek Wesolowski

Journal of Multivariate Analysis, 2001, vol. 77, issue 2, 163-174

Abstract: Problems of specification of discrete bivariate statistical models by a modified power series conditional distribution and a regression function are studied. An identifiability result for a wide class of such mixtures with infinite support is obtained. Also the finite support case within a more specific model is considered. Applications for Poisson, (truncated) geometric, and binomial mixtures are given. From the viewpoint of Bayesian analysis unique determination of the prior by a Bayes estimate of the mean for modified power series mixtures is investigated.

Keywords: modified power series distribution; identifiability of mixtures; posterior mean; regression function; characterization of probability distributions; Poisson mixture; geometric mixture; binomial mixture (search for similar items in EconPapers)
Date: 2001
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