A New Class of Composite Gbii Regression Models with Varying Threshold for Modelling Heavy-Tailed Data-Reference-Cited by-同舟云学术

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A New Class of Composite Gbii Regression Models with Varying Threshold for Modelling Heavy-Tailed Data

Published:2022 Issue: Volume: Page:
ISSN:1556-5068
Container-title:SSRN Electronic Journal
language:en
Short-container-title:SSRN Journal

Author:

Li Zhengxiao,WANG Fei,Zhao Zhengtang

Publisher

Elsevier BV

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference32 articles.

1. Log-skew-normal and log-skew-t distributions as models for family income data;Adelchi Azzalini;Journal of Income Distribution,2002

2. Modeling loss data using composite models;N A Sa Abu Bakar;Insurance: Mathematics and Economics,2015

3. Burr regression and portfolio segmentation;Jan Beirlant;Insurance: Mathematics and Economics,1998

4. Skew mixture models for loss distributions: a bayesian approach;Mauro Bernardi;Insurance: Mathematics and Economics,2012

5. On generalized log-moyal distribution: A new heavy tailed size distribution;Deepesh Bhati;Insurance: Mathematics and Economics,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A novel M-Lognormal–Burr regression model with varying threshold for modeling heavy-tailed claim severity data;Journal of Applied Statistics;2024-02-26

2. Generalized Linear Models;Springer Actuarial;2022-07-05

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