Kumaraswamy distribution: different methods of estimation

被引：53
作者：
Dey, Sanku [1 ]
Mazucheli, Josmar [2 ]
Nadarajah, Saralees [3 ]
机构：
[1] St Anthonys Coll, Shillong 793001, Meghalaya, India
[2] Univ Estadual Maringa, Maringa, Parana, Brazil
[3] Univ Manchester, Manchester M13 9PL, Lancs, England
来源：
COMPUTATIONAL & APPLIED MATHEMATICS | 2018年 / 37卷 / 02期
关键词：
Kumaraswamy distribution; Least squares estimators; Maximum likelihood estimators; Method of maximum product spacing; Method of moments estimators; Percentile estimators; Weighted least squares estimators; GENERALIZED EXPONENTIAL-DISTRIBUTION; BAYESIAN-ESTIMATION;
D O I：
10.1007/s40314-017-0441-1
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper addresses different methods of estimation of the unknown parameters of a two-parameter Kumaraswamy distribution from a frequentist point of view. We briefly describe ten different frequentist approaches, namely, maximum likelihood estimators, moments estimators, L-moments estimators, percentile based estimators, least squares estimators, weighted least squares estimators, maximum product of spacings estimators, Cramer-von-Mises estimators, Anderson-Darling estimators and right tailed Anderson-Darling estimators. Monte Carlo simulations and two real data applications are performed to compare the performances of the estimators for both small and large samples.
引用
收藏
页码：2094 / 2111
页数：18
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