Kumaraswamy Alpha Power Lomax Distribution: Properties and Applications in Actuarial Sciences

The Kumaraswamy alpha power Lomax model, a five-parameter sub-model of the Kumaraswamy alpha power transformed family, is explored in detail. It is of particular interest because there are a variety of possible symmetrical and asymmetrical forms for the density function of this distribution. The proposed distribution is loaded with several features. Maximum likelihood, least squares, weighted least squares, and Cramer-von Mises are the four techniques used to estimate the parameters of the new model. A simulation study has been conducted to assess its effectiveness. Actuarial measures like value at risk and tail value at risk are also derived. Compared to other recently introduced heavy-tailed distributions, the tail of the proposed distribution is heavier. Moreover, the model's usefulness is investigated using four real data sets from the fields of insurance, finance, and reliability. Compared to other well-known Lomax-based and competing distributions, the results demonstrate that the proposed distribution can fit the data better.

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Publication Details

Journal
Statistics Optimization & Information Computing
Published
2024-09-27
DOI
https://doi.org/10.19139/soic-2310-5070-2138
Citations
2
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
1.42
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article

Kumaraswamy Alpha Power Lomax Distribution: Properties and Applications in Actuarial Sciences

Harmanpreet Singh Kapoor, Kanchan Jain, Wondimu Fikre
2 citations
Statistics Optimization & Information Computing
Statistical Distribution Estimation and Applications
1.42
article

Kumaraswamy Alpha Power Lomax Distribution: Properties and Applications in Actuarial Sciences

Harmanpreet Singh Kapoor, Kanchan Jain, Wondimu Fikre
article en
2 citations

Abstract

The Kumaraswamy alpha power Lomax model, a five-parameter sub-model of the Kumaraswamy alpha power transformed family, is explored in detail. It is of particular interest because there are a variety of possible symmetrical and asymmetrical forms for the density function of this distribution. The proposed distribution is loaded with several features. Maximum likelihood, least squares, weighted least squares, and Cramer-von Mises are the four techniques used to estimate the parameters of the new model. A simulation study has been conducted to assess its effectiveness. Actuarial measures like value at risk and tail value at risk are also derived. Compared to other recently introduced heavy-tailed distributions, the tail of the proposed distribution is heavier. Moreover, the model's usefulness is investigated using four real data sets from the fields of insurance, finance, and reliability. Compared to other well-known Lomax-based and competing distributions, the results demonstrate that the proposed distribution can fit the data better.

Statistics Optimization & Information ComputingVol. 13(2)
Central University of Punjab (IN), University of Central Punjab (PK), Panjab University (IN)
Openalex Percentile: Top 15%
Statistical Distribution Estimation and Applications
1.42
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Kumaraswamy Alpha Power Lomax Distribution: Properties and Applications in Actuarial Sciences — Harmanpreet Singh Kapoor, Kanchan Jain, et al. · Statistics Optimization & Information Computing (2024) | TGRS Research Map | TGRS