A novel M-Lognormal–Burr regression model with varying threshold for modeling heavy-tailed claim severity data

IF 1.2 4区数学 Q2 STATISTICS & PROBABILITY

Journal of Applied Statistics Pub Date : 2024-02-26 DOI:10.1080/02664763.2024.2319232

Girish Aradhye, Deepesh Bhati, George Tzougas

引用次数: 0

Abstract

In this study, we explore the potential of composite probability distributions in effectively modeling claim severity data, which encompasses a spectrum of losses, ranging from minor to substantial...

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用于重尾理赔严重程度数据建模的具有不同阈值的新型 M-Lognormal-Burr 回归模型

在本研究中，我们探讨了复合概率分布在有效模拟索赔严重程度数据方面的潜力，这些数据涵盖了从轻微损失到重大损失的各种损失...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Applied Statistics 数学-统计学与概率论

CiteScore

3.40

自引率

0.00%

发文量

126

审稿时长

6 months

期刊介绍： Journal of Applied Statistics provides a forum for communication between both applied statisticians and users of applied statistical techniques across a wide range of disciplines. These areas include business, computing, economics, ecology, education, management, medicine, operational research and sociology, but papers from other areas are also considered. The editorial policy is to publish rigorous but clear and accessible papers on applied techniques. Purely theoretical papers are avoided but those on theoretical developments which clearly demonstrate significant applied potential are welcomed. Each paper is submitted to at least two independent referees.