Optimal Designs for Generalized Pareto Model

被引：0
|
作者：
Singh, Poonam [1 ]
Kumar, Ashok [2 ]
机构：
[1] Univ Delhi, Dept Stat, Delhi, India
[2] Univ Lucknow, Dept Stat, Lucknow, Uttar Pradesh, India
来源：
INTERNATIONAL JOURNAL OF MATHEMATICAL ENGINEERING AND MANAGEMENT SCIENCES | 2019年 / 4卷 / 05期
关键词：
Fisher information matrix; Local optimality; D-optimality; minimally supported designs; Tchebycheff system; REGRESSION;
D O I：
10.33889/IJMEMS.2019.4.5-100
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The generalized Pareto model plays an important role in modelling extreme events. Hosking and Wallis (1987) discussed the parameter and quantile estimation for generalized Pareto distribution. Optimal experimental designs are used to accurately estimate the unknown parameters of the model. In this paper, locally D-, A- and E-optimal designs with two and three support points having equal and unequal weights for homoscedastic generalized Pareto regression model are obtained numerically. It is also proved that these designs are minimally supported. The results are illustrated through Norwegian fire insurance claim data.
引用
收藏
页码：1264 / 1276
页数：13
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