Improving Model Fitting for Applicable Medical Data: A Novel Exponentiated Transformation of BURR XII

Authors

  • Ali Algarni Department of Statistics, King Abdulaziz University, Jeddah, Saudi Arabia

DOI:

https://doi.org/10.37256/cm.6220255666

Keywords:

maximum likelihood estimation (MLE), order statistics, BURR XII, ETBXII

Abstract

This paper presents a novel extension of the Exponentiated Transformation of the BURR XII (ETBXII) distribution. In this paper, we explore the need for improved model fitting to applicable data and present a literature review on existing distributions that researchers modified. The proposed extension is introduced, and its properties, such as its hazard rate and distribution function, are addressed. The results demonstrate that the suggested extension can better match data than existing distributions and present an empirical application to demonstrate its utility. The conclusion of the manuscript discusses the potential effects of the suggested expansion on statistical modelling in several domains.

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Published

2025-03-18

How to Cite

1.
Algarni A. Improving Model Fitting for Applicable Medical Data: A Novel Exponentiated Transformation of BURR XII. Contemp. Math. [Internet]. 2025 Mar. 18 [cited 2025 Apr. 2];6(2):1898-913. Available from: https://ojs.wiserpub.com/index.php/CM/article/view/5666