Modeling Vehicle Insurance Loss Data Using a New Member of T-X Family of Distributions
- https://doi.org/10.2991/jsta.d.200421.001How to use a DOI?
- Heavy-tailed distributions, Weibull distribution, Insurance losses, Actuarial measures, Monte Carlo simulation, Estimation
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.
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- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - Zubair Ahmad AU - Eisa Mahmoudi AU - Sanku Dey AU - Saima K. Khosa PY - 2020 DA - 2020/05 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 - https://doi.org/10.2991/jsta.d.200421.001 ID - Ahmad2020 ER -