Misgiyati, Misgiyati and Nisa, Khoirin and Warsono, Warsono (2017) Bayesian Inference of Poisson Distribution using Conjugate and Non-Informative Priors. Prosiding Seminar Nasional METODE KUANTITATIF 2017. ISSN 978-602-98559-3-7


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Poisson distribution is one of the most important and widely used statistical distributions. It is commonly used to describe the frequency probability of specific events when the average probability of a single occurrence within a given time interval is known. In this paper, Bayesian inference of Poisson distribution parameter (μ) is presented. Two Bayesian estimators of μ using two different priors are derived, one by using conjugate prior by applying gamma distribution, and the other using non-informative prior by applying Jeffery prior. The two priors yield the same posterior distributions namely gamma distribution. Comparison of the two Bayesian estimators is conducted through their bias and mean square error evaluation.

Item Type: Article
Subjects: H Social Sciences > HA Statistics
Depositing User: DR. KHOIRIN NISA
Date Deposited: 27 Mar 2018 04:42
Last Modified: 27 Mar 2018 04:42
URI: http://repository.lppm.unila.ac.id/id/eprint/6649

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