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ARTICLE
On Modeling the Medical Care Insurance Data via a New Statistical Model
Yen Liang Tung1, Zubair Ahmad2,*, G. G. Hamedani3
1 Accounting Department, School of Business, Nanjing University, Nanjing, China
2 Department of Statistics, Yazd University, Yazd, Iran
3 Department of Mathematical and Statistical Sciences, Marquette University, Milwaukee, USA
* Corresponding Author: Zubair Ahmad. Email:
Computers, Materials & Continua 2021, 66(1), 113-126. https://doi.org/10.32604/cmc.2020.012780
Received 12 July 2020; Accepted 12 August 2020; Issue published 30 October 2020
Abstract
Proposing new statistical distributions which are more flexible than the
existing distributions have become a recent trend in the practice of distribution
theory. Actuaries often search for new and appropriate statistical models to
address data related to financial and risk management problems. In the present
study, an extension of the Lomax distribution is proposed via using the approach
of the weighted T-X family of distributions. The mathematical properties along
with the characterization of the new model via truncated moments are derived.
The model parameters are estimated via a prominent approach called the maximum likelihood estimation method. A brief Monte Carlo simulation study to
assess the performance of the model parameters is conducted. An application to
medical care insurance data is provided to illustrate the potentials of the newly
proposed extension of the Lomax distribution. The comparison of the proposed
model is made with the (i) Two-parameter Lomax distribution, (ii) Three-parameter
models called the half logistic Lomax and exponentiated Lomax distributions, and
(iii) A four-parameter model called the Kumaraswamy Lomax distribution. The
statistical analysis indicates that the proposed model performs better than the competitive models in analyzing data in financial and actuarial sciences.
Keywords
Cite This Article
APA Style
Tung, Y.L., Ahmad, Z., Hamedani, G.G. (2021). On modeling the medical care insurance data via a new statistical model. Computers, Materials & Continua, 66(1), 113-126. https://doi.org/10.32604/cmc.2020.012780
Vancouver Style
Tung YL, Ahmad Z, Hamedani GG. On modeling the medical care insurance data via a new statistical model. Comput Mater Contin. 2021;66(1):113-126 https://doi.org/10.32604/cmc.2020.012780
IEEE Style
Y.L. Tung, Z. Ahmad, and G.G. Hamedani "On Modeling the Medical Care Insurance Data via a New Statistical Model," Comput. Mater. Contin., vol. 66, no. 1, pp. 113-126. 2021. https://doi.org/10.32604/cmc.2020.012780
Citations