Identifiability of mixtures of power-series distributions and related characterizations
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DOI: 10.1007/BF00773394
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Cited by:
- Gupta Arjun K. & Wesolowski Jacek, 2001. "Regressional Identifiability And Identification For Beta Mixtures," Statistics & Risk Modeling, De Gruyter, vol. 19(1), pages 71-82, January.
- Dimitri Karlis & Valentin Patilea, 2004. "Bootstrap Confidence Intervals in Mixtures of Discrete Distributions," Working Papers 2004-06, Center for Research in Economics and Statistics.
- Tin Lok James Ng & Thomas Brendan Murphy, 2021. "Model-based Clustering of Count Processes," Journal of Classification, Springer;The Classification Society, vol. 38(2), pages 188-211, July.
- Gupta, Arjun K. & Nguyen, Truc T. & Wang, Yinning & Wesolowski, Jacek, 2001. "Identifiability of Modified Power Series Mixtures via Posterior Means," Journal of Multivariate Analysis, Elsevier, vol. 77(2), pages 163-174, May.
- Burda, Martin & Harding, Matthew & Hausman, Jerry, 2012. "A Poisson mixture model of discrete choice," Journal of Econometrics, Elsevier, vol. 166(2), pages 184-203.
- Papageorgiou, H. & Wesolowski, Jacek, 1997. "Posterior mean identifies the prior distribution in nb and related models," Statistics & Probability Letters, Elsevier, vol. 36(2), pages 127-134, December.
- Becker, Niels G. & Utev, Sergey, 2002. "Multivariate Discrete Distributions with a Product-Type Dependence," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 509-524, November.
- Miller Jeffrey W., 2023. "Consistency of mixture models with a prior on the number of components," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-9, January.
- Lillo Rodríguez, Rosa Elvira, 2000. "Identifiability of differentiable bayes estimators of the uniform scale parameter," DES - Working Papers. Statistics and Econometrics. WS 9857, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
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Keywords
Univariate and multivariate power-series distributions; mixtures of distributions; the moment problem; infinite divisibility; posterior expectations;All these keywords.
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