One-Parameter Finite Mixture Distributions: Which Flexible Distribution to Use?

Abdul-Lateef Abukari

doi:10.14419/5128tj58

Authors and Affiliations

Abdul-Lateef Abukari Department of Economics and Actuarial Science, Faculty of Accounting and Finance, ‎University of Professional Studies, Accra

About this article

DOI:

https://doi.org/10.14419/5128tj58

Received:

18-04-2026

Accepted:

10-07-2026

Published:

18-07-2026

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Keywords:

Biomedical Science; Akash Distribution; Data Analysis; Mean Residual Function; Information ‎Criterion

Abstract

Single-parameter distributions hold significant value as they serve as fundamental models for ‎developing future distributions. This manuscript evaluates and meticulously compares the ‎performance of four one-parameter univariate continuous distributions. We do this by conducting a comprehensive numerical study to assess the performance of the Akash distribution against the performances of the Komal, New XLindley, and XGamma distributions. The density ‎functions of the considered distributions can be expressed as a convex amalgamation of ‎exponential and gamma distributions. Various structural properties of these distributions are discussed, including explicit expressions for the hazard rate, reversed hazard rate, cumulative hazard rate, moments, and quantile functions. We offer numerical examples to show the ‎flexibility of each model. These distributions are carefully assessed and analyzed in terms of ‎information criteria, providing valuable insights into the practical application of the distributions ‎in statistical modeling and data analysis contexts. The Akash distribution is a strong candidate ‎for applications in environmental science, biomedical science, and reliability engineering ‎datasets, compared to other one-parameter distributions reviewed in this article‎.

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