A New Inverse Rayleigh Distribution with Applications of COVID-19 Data: Properties, Estimation Methods and Censored Sample

被引：3

作者：

El-Sherpieny, El-Sayed A. ^{[1
]}

Muhammed, Hiba Z. ^{[1
]}

Almetwally, Ehab M. ^{[2
,3
]}

机构：

[1] Cairo Univ, Fac Grad Studies Stat Res, Giza, Egypt

[2] Imam Mohammad Ibn Saud Islamic Univ IMSIU, Fac Sci, Dept Math & Stat, Riyadh 11432, Saudi Arabia

[3] Delta Univ Sci & Technol, Fac Business Adm, Dakahlia, Egypt

来源：

ELECTRONIC JOURNAL OF APPLIED STATISTICAL ANALYSIS | 2023年 / 16卷 / 02期

关键词：

key Odd Weibull family; inverted Rayleigh distribution; maximum product spacing; Bayesian estimation; COVID-19; censored sample; EXPONENTIAL-DISTRIBUTION; PARAMETERS; PRODUCT;

D O I：

10.1285/i20705948v16n2p449

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：

This paper aims at modeling the COVID-19 spread in the United Kingdom and United States of America, by specifying an optimal statistical univarite model. A new lifetime distribution with three-parameters is introduced by a combination of inverse Rayleigh distribution and odd Weibull family of distributions to formulate the odd Weibull inverse Rayleigh (OWIR) distribution. Some of the mathematical properties of the OWIR distribution are discussed as linear representation, quantile, moments, function of moment production, hazard rate, stress-strength reliability, and order statistics. Maximum likelihood, maximum product spacing, and Bayesian estimation method are applied to estimate the unknown parameters of OWIR distribution. The parameters of the OWIR distribution are estimated under progressive type -II censoring scheme with random removal. A numerical results of a Monte Carlo simulation is obtained to assess the use of estimation methods.

引用

页码：449 / 472

页数：25

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