A Comparative Study of Maximum Likelihood Estimation and Bayesian Estimation for Erlang Distribution and Its Applications

Kaisar Ahmad, Sheikh Parvaiz Ahmad
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引用次数: 3

Abstract

In this chapter, Erlang distribution is considered. For parameter estimation, maximum likelihood method of estimation, method of moments and Bayesian method of estimation are applied. In Bayesian methodology, different prior distributions are employed under various loss functions to estimate the rate parameter of Erlang distribution. At the end the simulation study is conducted in R-Software to compare these methods by using mean square error with varying sample sizes. Also the real life applications are examined in order to compare the behavior of the data sets in the parametric estimation. The comparison is also done among the different loss functions.
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Erlang分布的极大似然估计与贝叶斯估计的比较研究及其应用
在本章中,考虑Erlang发行。参数估计采用极大似然估计法、矩量法和贝叶斯估计法。在贝叶斯方法中,在不同的损失函数下采用不同的先验分布来估计Erlang分布的速率参数。最后在R-Software中进行了仿真研究,利用不同样本量的均方误差对这些方法进行了比较。为了比较参数估计中数据集的行为,还研究了实际应用。并对不同的损失函数进行了比较。
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Introductory Chapter: Ramifications of Incomplete Knowledge Asymptotic Normality of Hill’s Estimator under Weak Dependence Methods of Russian Patent Analysis Development of Estimation Procedure of Population Mean in Two-Phase Stratified Sampling A Comparative Study of Maximum Likelihood Estimation and Bayesian Estimation for Erlang Distribution and Its Applications
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