Modeling Vehicle Insurance Loss Data Using a New Member of T-X Family of Distributions

DOI

10.2991/jsta.d.200421.001How to use a DOI?

Keywords

Heavy-tailed distributions; Weibull distribution; Insurance losses; Actuarial measures; Monte Carlo simulation; Estimation

Abstract

In actuarial literature, we come across a diverse range of probability distributions for fitting insurance loss data. Popular distributions are lognormal, log-t, various versions of Pareto, log-logistic, Weibull, gamma and its variants and a generalized beta of the second kind, among others. In this paper, we try to supplement the distribution theory literature by incorporating the heavy tailed model, called weighted T-X Weibull distribution. The proposed distribution exhibits desirable properties relevant to the actuarial science and inference. Shapes of the density function and key distributional properties of the weighted T-X Weibull distribution are presented. Some actuarial measures such as value at risk, tail value at risk, tail variance and tail variance premium are calculated. A simulation study based on the actuarial measures is provided. Finally, the proposed method is illustrated via analyzing vehicle insurance loss data.

Copyright

© 2020 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)
View full text (HTML)

TY  - JOUR
AU  - Zubair Ahmad
AU  - Eisa Mahmoudi
AU  - Sanku Dey
AU  - Saima K. Khosa
PY  - 2020
DA  - 2020/05/28
TI  - Modeling Vehicle Insurance Loss Data Using a New Member of T-X Family of Distributions
JO  - Journal of Statistical Theory and Applications
SP  - 133
EP  - 147
VL  - 19
IS  - 2
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.200421.001
DO  - 10.2991/jsta.d.200421.001
ID  - Ahmad2020
ER  -