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On the contaminated exponential distribution: A theoretical Bayesian approach for modeling positive-valued insurance claim data with outliers

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  • Okhli, Kheirolah
  • Jabbari Nooghabi, Mehdi

Abstract

Analysis of the insurance data has recently been achieved considerable attention for insurance industries. This paper introduces the contaminated exponential (CE) distribution as an alternative platform for analyzing positive-valued insurance dataset with some levels of outliers. The Bayesian approach for obtaining the parameter estimates is presented. In order to check the performance of the proposed methodology, some simulation studies by implementing the Gibbs sampling are conducted. Finally, four examples of actual insurance claim data with various sample sizes have been analyzed to illustrate the superiority of the CE distribution in analyzing data and identifying outliers.

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  • Okhli, Kheirolah & Jabbari Nooghabi, Mehdi, 2021. "On the contaminated exponential distribution: A theoretical Bayesian approach for modeling positive-valued insurance claim data with outliers," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    • Handle: RePEc:eee:apmaco:v:392:y:2021:i:c:s0096300320306652
    DOI: 10.1016/j.amc.2020.125712
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    Cited by:

    1. Abbas Mahdavi & Omid Kharazmi & Javier E. Contreras-Reyes, 2022. "On the Contaminated Weighted Exponential Distribution: Applications to Modeling Insurance Claim Data," JRFM, MDPI, vol. 15(11), pages 1-18, October.
    2. Okhli, Kheirolah & Jabbari Nooghabi, Mehdi, 2023. "On the three-component mixture of exponential distributions: A Bayesian framework to model data with multiple lower and upper outliers," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 480-500.
    3. Mehdi Jabbari Nooghabi, 2021. "Comparing estimation of the parameters of distribution of the root density of plants in the presence of outliers," Environmetrics, John Wiley & Sons, Ltd., vol. 32(5), August.

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