Statistical Analysis of COVID-19 Data: Using A New Univariate and Bivariate Statistical Model. (23rd June 2022)

• Record Type: Journal Article
• Authors: Bantan, Rashad A. R.; Shafiq, Shakaiba; Tahir, M. H.; Elhassanein, Ahmed; Jamal, Farrukh; Almutiry, Waleed; Elgarhy, Mohammed
• Other Names: Gulzar Muhammad Academic Editor.
• Is Part Of: Journal of function spaces. Volume 2022(2022)
• Publication Date: 2022-06-23
• Subjects: Function spaces -- Periodicals; 515.7305
• DOI: 10.1155/2022/2851352
• Languages: English
• ISSNs: 2314-8896

Abstract

Abstract : 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.