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Showing 2 results for Yaghoobzadeh Shahrastani
Shahrastani Shahram Yaghoobzadeh Shahrastani,
Volume 23, Issue 2 (3-2019)
Abstract
In this paper, a new estimate of exponential type of auxiliary information to help simple random sampling without replacement of the finite population mean is introduced. This new estimator with a few other estimates using two real data sets are compared with the mean square error.
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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