Two-parameter Rayleigh distribution: Different methods of estimation

被引:2
|
作者
机构
[1] Department of Statistics, St. Anthony's College, Shillong, Meghalaya
[2] Department of Mathematics, Jones Hall, College of William and Mary, Williamsburg, VA
[3] Department of Mathematics and Statistics, Indian Institute of Technology, Kanpur
来源
Dey, S. (sanku.dey2k2003@yahoo.co.in) | 1600年 / American Sciences Press Inc.卷 / 33期
关键词
Asymptotic distribution; Bayes estimators; L-moment estimators; Least squares estimators; Maximum likelihood estimators; Method of moment estimators; Percentile-based estimators; Simulation consistent estimators; Weighted least squares estimators;
D O I
10.1080/01966324.2013.878676
中图分类号
学科分类号
摘要
In this study we have considered different methods of estimation of the unknown parameters of a two-parameter Rayleigh distribution from both the frequentists' and the Bayesian view points. First, we briefly describe different frequentists' approaches: maximum likelihood estimators, method of moments estimators, L- moment estimators, percentile-based estimators, and least squares estimators, and we compare them using extensive numerical simulations. We have also considered Bayesian inferences of the unknown parameters. It is observed that the Bayes estimates and the associated credible intervals cannot be obtained in explicit forms, and we have suggested using an importance sampling technique to compute the Bayes estimates and the associated credible intervals. We analyze one dataset for illustrative purposes. 2014 Copyright © Taylor & Francis Group.
引用
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页码:55 / 74
页数:19
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