Markov Logarithmic Series Distribution and Estimation of its Parameters by Method of E-Bayesian
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Abstract: (3201 Views) |
In the analysis of Bernoulli's variables, an investigation of the their dependence is of the prime importance. In this paper, the distribution of the Markov logarithmic series is introduced by the execution of the first-order dependence among Bernoulli variables. In order to estimate the parameters of this distribution, maximum likelihood, moment, Bayesian and also a new method which called the expected Bayesian method (E-Bayesian) are employed. In continuation, using a simulation study, it is shown that the expected Bayesian estimator out performed over the other estimators. |
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Keywords: Markov Logarithmic Series Distribution, Bayesian Estimation, E-Bayes Estimation, Maximum Likelihood Estimation, Moment Estimation, Mean Square Error. |
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Full-Text [PDF 237 kb]
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Type of Study: Research |
Subject:
Special Received: 2019/04/23 | Accepted: 2020/05/21 | Published: 2020/06/6
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