New exponentiated -Weibull -G family: Properties, simulations, regression and applications to COVID-19 data

被引：0

作者：

Cordeiro, Gauss M. ^{[1
]}

Biazatti, Elisangela c. ^{[1
,2
]}

De Lima, Maria do Carmo s. ^{[1
]}

De Santana, Luis H. ^{[3
]}

机构：

[1] Univ Fed Pernambuco, Dept Stat, Recife, Brazil

[2] Fed Univ Rondonia, Dept Math & Stat, Ji Parana, PR, Brazil

[3] Univ Estadual Maringa, Technol Dept, Umuarama, Brazil

来源：

CHILEAN JOURNAL OF STATISTICS | 2023年 / 14卷 / 02期

关键词：

Exponentiated-Weibull distribution; Generalized distributions; Maximum likelihood estimation; Moment; T-X family; BETA; MODEL;

D O I：

10.32372/ChJS.14-02-03

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this article, a new exponentiated-Weibull-G family with two extra shape parameters is defined, which incorporates certain special classes of distributions. Some of its mathematical properties are presented. Maximum likelihood estimation and simulations are addressed. Two applications to COVID-19 data show the flexibility of the new family. A simulation experiment is developed to show the validity of the asymptotic properties of the maximum likelihood estimators. A regression model, called the log-exponentiated Weibull-Weibull, is constructed and applied to COVID-19 data, which has better performance when compared to two other regression models.

引用

页码：99 / 122

页数：24

共 29 条

[1] A new method for generating families of continuous distributions [J].