:: Volume 24, Issue 2 (3-2020) ::
Andishe 2020, 24(2): 1-8 Back to browse issues page
Markov Logarithmic Series Distribution and Estimation of its Parameters by Method of E-Bayesian
Abstract:   (2553 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.

Keywords: Markov Logarithmic Series Distribution, Bayesian Estimation, E-Bayes Estimation, Maximum Likelihood Estimation, Moment Estimation, Mean Square Error.
Full-Text [PDF 237 kb]   (928 Downloads)    
Type of Study: Research | Subject: Special
Received: 2019/04/23 | Accepted: 2020/05/21 | Published: 2020/06/6


XML   Persian Abstract   Print



Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 24, Issue 2 (3-2020) Back to browse issues page