The new continuous distribution : Statistical properties and modelling for Covid-19 data

Our research unveils a transformative distribution model: the Kumaraswamy power burr distribution. This innovative model emerges through the application of the Kumaraswamy transformation to the power burr distribution. We meticulously outline the probability and distribution functions, supported by compelling graphs and a rigorous mathematical foundation for the probability function of this novel distribution. In addition, we offer detailed equations and an extensive analysis of the statistical properties of this distribution. Parameter estimation is skillfully executed using the maximum likelihood estimation (MLE) method. Our compelling evidence shows that this newly created distribution not only enhances accuracy but also outperforms existing models significantly in analyzing COVID-19 data.

Authors

Publication Details

Journal
Journal of Statistics and Management Systems
Published
2025-01-01
DOI
https://doi.org/10.47974/jsms-1371
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
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article

The new continuous distribution : Statistical properties and modelling for Covid-19 data

Ayşe Meti̇n Karakaş
Journal of Statistics and Management Systems
COVID-19 epidemiological studies
article

The new continuous distribution : Statistical properties and modelling for Covid-19 data

Ayşe Meti̇n Karakaş
article en

Abstract

Our research unveils a transformative distribution model: the Kumaraswamy power burr distribution. This innovative model emerges through the application of the Kumaraswamy transformation to the power burr distribution. We meticulously outline the probability and distribution functions, supported by compelling graphs and a rigorous mathematical foundation for the probability function of this novel distribution. In addition, we offer detailed equations and an extensive analysis of the statistical properties of this distribution. Parameter estimation is skillfully executed using the maximum likelihood estimation (MLE) method. Our compelling evidence shows that this newly created distribution not only enhances accuracy but also outperforms existing models significantly in analyzing COVID-19 data.

Journal of Statistics and Management SystemsVol. 28(4)
Openalex Percentile: Top 88%
COVID-19 epidemiological studies
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