A New Inverse Extended Weibull Distribution for Modelling Insurance Loss Data

被引：0

作者：

Yu, Shilin ^{[1
]}

Li, Xuan ^{[1
]}

Choy, S. T. Boris ^{[1
]}

机构：

[1] Univ Sydney, Discipline Business Analyt, Sydney, NSW 2006, Australia

来源：

INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2023年 / 31卷 / SUPP02期

关键词：

Insurance data; Weibull-type distributions; extreme value distributions; maximum likelihood estimation; Akaike information criterion; FAMILY;

D O I：

10.1142/S0218488523400196

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper proposes a new three-parameter inverse Weibull-type distribution via a similar way of constructing a skew normal distribution. The additional shape parameter increases the distribution's modelling capability as other three-parameter inverse Weibull-type distributions. The mathematical properties of this inverse extended Weibull distribution are studied and proven. In the empirical study of four insurance datasets from Australia, Denmark and the USA, we show that the proposed distribution performs very well compared with other three-parameter competitors.

引用

页码：307 / 322

页数：16

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