Improved Shape Parameter Estimation for the Three-Parameter Log-Logistic Distribution

被引:1
|
作者
Mateus, Ayana [1 ,2 ,3 ]
Caeiro, Frederico [1 ,2 ,3 ]
机构
[1] NOVA Univ Lisbon, NOVA Sch Sci & Technol FCT NOVA, Caparica, Portugal
[2] FCT NOVA, Ctr Math & Applicat CMA, Caparica, Portugal
[3] Dept Math, Caparica, Portugal
关键词
THRESHOLD SELECTION; TAIL INDEX; STATISTICS; EXPONENT;
D O I
10.1155/2022/8400130
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The log-logistic distribution is widely used in different fields of study such as survival analysis, hydrology, insurance, and economics. Recently, Ahsanullah and Alzaatreh studied the best linear unbiased estimators for the location and the scale parameters of the three-parameter log-logistic model. The same authors also propose a shift-invariant Hill estimator for the unknown shape parameter. In this work, we propose a new estimation method for the shape parameter. We derive its nondegenerate asymptotic behaviour and analyse its finite sample performance through a Monte Carlo simulation study. To have precise estimates, we present a method for selecting the threshold. To illustrate the improvement achieved, efficiency comparisons are also provided.
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页数:13
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