Far East Journal of Theoretical Statistics

The Far East Journal of Theoretical Statistics publishes original research papers and survey articles in the field of theoretical statistics, covering topics such as Bayesian analysis, multivariate analysis, and stochastic processes.

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THE AKRONG DISTRIBUTION: A NOVEL BOUNDED LINEAR PROBABILITY MODEL FOR ENHANCED ACCURACY AND UNBIASED ESTIMATION IN INSURANCE CLAIM MODELING WITH POLICY LIMITS

Authors

  • Christian Akrong Hesse
  • Evans Tee
  • Emmanuel Dodzi Kpeglo
  • Dominic Buer Boyetey

Keywords:

actuarial modeling, Akrong distribution, bounded distribution, insurance claims, policy limits

DOI:

https://doi.org/10.17654/0972086325013

Abstract

This paper proposes and introduces the novel Akrong probability distribution, a bounded-form model specifically designed to accurately represent insurance claim payments subject to policy limits. Unlike traditional heavy-tailed approaches, the Akrong distribution explicitly defines the policy limit as a model parameter, offering a flexible and highly interpretable alternative. The distribution’s essential mathematical properties, such as the probability density function (pdf), cumulative distribution function (cdf), survival function, hazard rate function (hrf), and quantile function, are derived. Parameter estimates are obtained using both maximum likelihood and method of moments techniques. Through numerical experiments, the estimators demonstrate good performance and asymptotic behavior for finite sample sizes. The Akrong distribution exhibits desirable features such as an increasing hazard rate and significant shape adaptability through its parameters, proving its suitability for modeling systems characterized by rising risk over time.

Received: June 8, 2025
Accepted: August 20, 2025

References

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Published

2025-08-28

Issue

Section

Articles

How to Cite

THE AKRONG DISTRIBUTION: A NOVEL BOUNDED LINEAR PROBABILITY MODEL FOR ENHANCED ACCURACY AND UNBIASED ESTIMATION IN INSURANCE CLAIM MODELING WITH POLICY LIMITS. (2025). Far East Journal of Theoretical Statistics , 69(2), 259-279. https://doi.org/10.17654/0972086325013

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