Research on Mathematics Reported by a Researcher at Damietta University (Bayesian and Non-Bayesian Risk Analysis and Assessment under Left-Skewed Insurance Data and a Novel Compound Reciprocal Rayleigh Extension): Mathematics

2023 APR 18 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New study results on mathematics have been published. According to news reporting out of Damietta University by NewsRx editors, research stated, “Continuous probability distributions can handle and express different data within the modeling process. Continuous probability distributions can be used in the disclosure and evaluation of risks through a set of well-known basic risk indicators.”

Financial supporters for this research include King Saud University.

Our news editors obtained a quote from the research from Damietta University: “In this work, a new compound continuous probability extension of the reciprocal Rayleigh distribution is introduced for data modeling and risk analysis. Some of its properties including are derived. The estimation of the parameters is carried out via different techniques. Bayesian estimations are computed under gamma and normal prior. The performance and assessment of all techniques are studied and assessed through Monte Carlo experiments of simulations and two real-life datasets for applications. Two applications to real datasets are provided for comparing the new model with other competitive models and to illustrate the importance of the proposed model via the maximum likelihood technique. Numerical analysis for expected value, variance, skewness, and kurtosis are given.”

According to the news editors, the research concluded: “Five key risk indicators are defined and analyzed under Bayesian and non-Bayesian estimation. An extensive analytical study that investigated the capacity to reveal actuarial hazards used a wide range of well-known models to examine actuarial disclosure models. Using actuarial data, actuarial hazards were evaluated and rated.”

For more information on this research see: Bayesian and Non-Bayesian Risk Analysis and Assessment under Left-Skewed Insurance Data and a Novel Compound Reciprocal Rayleigh Extension. Mathematics, 2023,11(7). (Mathematics - http://www.mdpi.com/journal/mathematics). The publisher for Mathematics is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/math11071593.

Our news journalists report that additional information may be obtained by contacting Mohamed Ibrahim, Department of Applied, Mathematical and Actuarial Statistics, Faculty of Commerce, Damietta University, Damietta 34517, Egypt. Additional authors for this research include Walid Emam, Yusra Tashkandy, M. Masoom Ali, Haitham M. Yousof.

ORCID is an identifier for authors and includes bibliographic information. The following is ORCID information for the authors of this research: Mohamed Ibrahim (http://orcid.org/0000-0003-4893-9669), Walid Emam (http://orcid.org/0000-0002-6810-6640), Yusra Tashkandy (http://orcid.org/0000-0003-2878-4460), M. Masoom Ali (http://orcid.org/0000-0002-0120-9442), Haitham M. Yousof (http://orcid.org/0000-0003-4589-4944).

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