Statistical Analysis of COVID-19 Data: Using A New Univariate and Bivariate Statistical Model

Autor: Rashad A. R. Bantan, Shakaiba Shafiq, M. H. Tahir, Ahmed Elhassanein, Farrukh Jamal, Waleed Almutiry, Mohammed Elgarhy
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Journal of Function Spaces, Vol 2022 (2022)
Druh dokumentu: article
ISSN: 2314-8888
DOI: 10.1155/2022/2851352
Popis: In this paper, a new distribution named as unit-power Weibull distribution (UPWD) defined on interval (0,1) is introduced using an appropriate transformation to the positive random variable of the Weibull distribution. This work offers quantile function, linear representation of the density, ordinary and incomplete moments, moment-generating function, probability-weighted moments, L-moments, TL-moments, Rényi entropy, and MLE estimation. Additionally, several actuarial measures are computed. The real data applications are carried out to underline the practical usefulness of the model. In addition, a bivariate extension for the univariate power Weibull distribution named as bivariate unit-power Weibull distribution (BIUPWD) is also configured. To elucidate the bivariate extension, simulation analysis and application using COVID-19-associated fatality rate data from Italy and Belgium to conform a BIUPW distribution with visual depictions are also presented.
Databáze: Directory of Open Access Journals
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