COMPARISONS OF SIX DIFFERENT ESTIMATION METHODS FOR LOG-KUMARASWAMY DISTRIBUTION

被引:1
|
作者
Tanis, Caner [1 ]
Saracoglu, Bugra [1 ]
机构
[1] Selcuk Univ, Fac Sci, Konya, Turkey
来源
THERMAL SCIENCE | 2019年 / 23卷
关键词
log-Kumaraswamy distribution; maximum likelihood estimation; Cramer-von-Mises estimation method; least-squares estimation; percentile estimation; Monte-Carlo simulation; GENERALIZED EXPONENTIAL-DISTRIBUTION;
D O I
10.2298/TSCI190411344T
中图分类号
O414.1 [热力学];
学科分类号
摘要
In this paper, it is considered the problem of estimation of unknown parameters of log-Kumaraswamy distribution via Monte-Carlo simulations. Firstly, it is described six different estimation methods such as maximum likelihood, approximate bayesian, least-squares, weighted least-squares, percentile, and Cramer-von-Mises. Then, it is performed a Monte-Carlo simulation study to evaluate the performances of these methods according to the biases and mean-squared errors of the estimators. Furthermore, two real data applications based on carbon fibers and the gauge lengths are presented to compare the fits of log-Kumaraswamy and other fitted statistical distributions.
引用
收藏
页码:S1839 / S1847
页数:9
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