1
Department of Mathematics, Imam Ali (AS) University of Science and Technology, Iran
2
Department of Statistics, Payam Noor University, Tehran, Iran
3
Department of Statistics, University of Tabriz, Iran
Abstract
In the analysis of Bernoulli variables, it is of great importance to examine the dependence between them. In this paper, by applying the first-order dependence between Bernoulli variables, the logarithmic Markov series distribution is introduced. To estimate the parameters of this distribution, maximum likelihood, moment, Bayesian methods, and also a new method called the expected Bayesian method (E-Bayesian) are used. In the following, it is shown using a simulation study that the expected Bayesian estimator performs better than other estimators.
Esfandiarifar, H., Nasiri, P. & Makoui, R. (2020). Distribution of logarithmic Markov series and estimation of its parameters using E-Bayesian method. Andishe_ye Amari, 24(2), 1-8.
MLA
Esfandiarifar, H., Nasiri, P., & Makoui, R. "Distribution of logarithmic Markov series and estimation of its parameters using E-Bayesian method", Andishe_ye Amari, 24, 2, 2020, 1-8.
HARVARD
Esfandiarifar H., Nasiri P., Makoui R. (2020). 'Distribution of logarithmic Markov series and estimation of its parameters using E-Bayesian method', Andishe_ye Amari, 24(2), pp. 1-8.
CHICAGO
H. Esfandiarifar, P. Nasiri & R. Makoui, "Distribution of logarithmic Markov series and estimation of its parameters using E-Bayesian method," Andishe_ye Amari, 24 2 (2020): 1-8,
VANCOUVER
Esfandiarifar H., Nasiri P., Makoui R. Distribution of logarithmic Markov series and estimation of its parameters using E-Bayesian method. Andishe_ye Amari. 2020;24(2):1-8 (In Persian).
