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Showing 6 results for Bayesian Estimation
Shahrastani Shahram Yaghoobzadeh,
Volume 21, Issue 2 (3-2017)
Abstract
In this study, E-Bayesian of parameters of two parameter exponential distribution under squared error loss function is obtained. The estimated and the efficiency of the proposed method has been compared with Bayesian estimator using Monte Carlo simulation.
Ali Shadrokh, Shahrastani Shahram Yaghoobzadeh,
Volume 24, Issue 1 (9-2019)
Abstract
In this study, E-Bayesian and hierarchical Bayesian of parameter of Rayleigh distribution under progressive type-II censoring sampales and the efficiency of the proposed methods has been compared with each and Bayesian estimator using Monte Carlo simulation.
Shahrastani Shahram Yaghoobzadeh,
Volume 24, Issue 1 (9-2019)
Abstract
In this paper, reliability in multi-component stress-strength models, when the stress and strength variables are inverse Rayleigh distributions with different parameters of alpha and beta. Estimates of the maximum likelihood, Bayesian and empirical Bayesian are estimated. Then, with the help of Monte Carlo simulation and two real data sets, these estimation methods are compared.
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Volume 24, Issue 2 (3-2020)
Abstract
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.
Dr. Shahram Yaghoobzadeh Shahrestani, Dr. Reza Zarei,
Volume 25, Issue 1 (1-2021)
Abstract
Whenever approximate and initial information about the unknown parameter of a distribution is available, the shrinkage estimation method can be used to estimate it. In this paper, first, the E-Bayesian estimation of the parameter of an inverse Rayleigh distribution under the general entropy loss function is obtained. Then, the shrinkage estimate of the inverse Rayleigh distribution parameter is investigated using the guess value. Also, using Monte Carlo simulations and a real data set, the proposed shrinkage estimation is compared with the UMVU and E-Bayesian estimators based on the relative efficiency criterion.
Shahrastani Shahram Yaghoobzadeh Shahrastani, Amrollah Jafari,
Volume 28, Issue 1 (9-2023)
Abstract
In this article, queunig model $M/M/1$ is Considered, in which the innterarrival of customers have an exponenial disributon with the parameter $lambda$ and the service times have an exponenial disributon with the parameter $mu$ and are independent of the interarrival times. it is also assumed that the system is active until $T$. Then, under this stopping time Bayesian, $E$-Bayesian and hierarchical Bayesian estimations of the traffic intensity parameter of this queuing model are obtained under the general entropy loss function and considering the gamma and erlang prior distributions for parameters $lambda$ and $mu$, respicctively. Then, using numerical analysis and based on a new index, Bayesian, $E$-Bayesian and hierarchical Bayesian estimations are compared.
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