Statistical Probability Distribution for the Covid-19 Mortality Rate.

In the study, a discrete distribution is proposed by considering the Poisson distribution as a base distribution and the Lindley distribution as a parametric distribution which is named as Poisson extended Lindley distribution (PELD). The new distribution is known as the Poisson extended Lindley distribution. Its density function, as well as its survival and hazard rate curves are shown graphically. The study presented the Moment generating function and its related measures such as moments about the origin and mean, coefficient of variation, skewness, and kurtosis. To calculate the distribution parameters, distinct estimating strategies are employed. In order to compare and draw conclusions about the performance of the different estimators, a thorough numerical analysis was done. Here, a real data set on the COVID-19 mortality rate was examined to show how adaptable and practical the suggested distribution is.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-05-08
DOI
https://doi.org/10.52783/jisem.v10i4.8667
Primary Topic
COVID-19 epidemiological studies
Type
article
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article

Statistical Probability Distribution for the Covid-19 Mortality Rate.

Lokesh Parashar
Journal of Information Systems Engineering & Management
COVID-19 epidemiological studies
article

Statistical Probability Distribution for the Covid-19 Mortality Rate.

Lokesh Parashar
article en

Abstract

In the study, a discrete distribution is proposed by considering the Poisson distribution as a base distribution and the Lindley distribution as a parametric distribution which is named as Poisson extended Lindley distribution (PELD). The new distribution is known as the Poisson extended Lindley distribution. Its density function, as well as its survival and hazard rate curves are shown graphically. The study presented the Moment generating function and its related measures such as moments about the origin and mean, coefficient of variation, skewness, and kurtosis. To calculate the distribution parameters, distinct estimating strategies are employed. In order to compare and draw conclusions about the performance of the different estimators, a thorough numerical analysis was done. Here, a real data set on the COVID-19 mortality rate was examined to show how adaptable and practical the suggested distribution is.

Journal of Information Systems Engineering & ManagementVol. 10(4)
Openalex Percentile: Top 88%
COVID-19 epidemiological studies
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