Weighted power Maxwell distribution: Statistical inference and COVID-19 applications

  • Muqrin A. Almuqrin
  • , Salemah A. Almutlak
  • , Ahmed M. Gemeay
  • , Ehab M. Almetwally
  • , Kadir Karakaya
  • , Nicholas Makumi
  • , Eslam Hussam
  • , Ramy Aldallal

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

During the course of this research, we came up with a brand new distribution that is superior; we then presented and analysed the mathematical properties of this distribution; finally, we assessed its fuzzy reliability function. Because the novel distribution provides a number of advantages, like the reality that its cumulative distribution function and probability density function both have a closed form, it is very useful in a wide range of disciplines that are related to data science. One of these fields is machine learning, which is a sub field of data science. We used both traditional methods and Bayesian methodologies in order to generate a large number of different estimates. A test setup might have been carried out to assess the effectiveness of both the classical and the Bayesian estimators. At last, three different sets of Covid-19 death analysis were done so that the effectiveness of the new model could be demonstrated.

Original languageEnglish
Article numbere0278659
JournalPLoS ONE
Volume18
Issue number1 January
DOIs
StatePublished - Jan 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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