The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data

被引：44

作者：

Almetwally E.M. ^{[1
]}

机构：

[1] Department of Statistics, Faculty of Business Administration, Delta University of Science and Technology, Belkas

来源：

Annals of Data Science | 2022年 / 9卷 / 01期

关键词：

COVID-19; Inverted Topp–Leone distribution; Maximum likelihood estimation; Maximum product spacing; Odd Weibull family;

D O I：

10.1007/s40745-021-00329-w

中图分类号：

学科分类号：

摘要：

This paper aims at defining an optimal statistical model for the COVID-19 distribution in the United Kingdom, and Canada. A combining the inverted Topp–Leone distribution and the odd Weibull family introduces a new lifetime distribution with a three-parameter to formulate the odd Weibull inverted Topp–Leone (OWITL) distribution. As a simple linear representation, hazard rate function, and moment function, this new distribution has several nice properties. To estimate the unknown parameters of OWITL distribution, maximum likelihood, least-square, weighted least-squares, maximum product spacing, Cramér–von Mises estimators, and Anderson–Darling estimation methods are used. To evaluate the use of estimation techniques, a numerical outcome of the Monte Carlo simulation is obtained. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

引用

页码：121 / 140

页数：19

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