JOURNAL ARTICLE

Maximum Likelihood Estimation from Grouped Poisson Data

Walter H. CarterJacob Van BowenRaymond H. Myers

Year: 1971 Journal:   Journal of the American Statistical Association Vol: 66 (334)Pages: 351-351

Abstract

Abstract In this article, sufficient conditions are given for the existence of a unique solution of the likelihood equation which results from a grouped data sample. The necessary and sufficient conditions for the convergence of a sequence defined by the method of successive approximations to this unique solution are also given. Finally, it is shown that when the groups from an underlying Poisson distribution are connected the method of successive approximations will converge to the unique solution of the resulting likelihood equation regardless of the starting value chosen provided that the sample is not concentrated entirely in either or both the first and last groups.

Keywords:
Mathematics Poisson distribution Sequence (biology) Applied mathematics Maximum likelihood Convergence (economics) Statistics Sample (material) Maximum likelihood sequence estimation Distribution (mathematics) Quasi-likelihood Count data Mathematical analysis

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Citation History

Topics

Bayesian Methods and Mixture Models
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Statistical Methods and Models
Physical Sciences →  Mathematics →  Statistics and Probability
Statistical Methods and Inference
Physical Sciences →  Mathematics →  Statistics and Probability

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