Marshall-Olkin Alpha Power Weibull Distribution: Different Methods of Estimation Based on Type-I and Type-II Censoring

被引：24

作者：

Almetwally, Ehab M. ^{[1
]}

Sabry, Mohamed A. H. ^{[2
]}

Alharbi, Randa ^{[3
]}

Alnagar, Dalia ^{[3
]}

Mubarak, Sh A. M. ^{[4
]}

Hafez, E. H. ^{[5
]}

机构：

[1] Delta Univ Sci & Technol, Fac Business Adm, Mansoura, Egypt

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

[3] Univ Tabuk, Dept Stat, Tabuk, Saudi Arabia

[4] High Inst Engn & Technol, Minist Higher Educ, El Minia, Egypt

[5] Helwan Univ, Fac Sci, Dept Math, Cairo, Egypt

来源：

COMPLEXITY | 2021年 / 2021卷

关键词：

MAXIMUM-LIKELIHOOD; LOMAX DISTRIBUTION; FAMILY; PARAMETER;

D O I：

10.1155/2021/5533799

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

This paper introduces the new novel four-parameter Weibull distribution named as the Marshall-Olkin alpha power Weibull (MOAPW) distribution. Some statistical properties of the distribution are examined. Based on Type-I censored and Type-II censored samples, maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation for the MOAPW distribution parameters are discussed. Numerical analysis using real data sets and Monte Carlo simulation are accomplished to compare various estimation methods. This novel model's supremacy upon some famous distributions is explained using two real data sets and it is shown that the MOAPW model can achieve better fits than other competitive distributions.

引用

页数：18

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