Classical and Bayesian Inference of Conditional Stress-Strength Model under Kumaraswamy Distribution

被引：0

作者：

Riad, Fathy H. ^{[1
,2
]}

Saber, Mohammad Mehdi ^{[3
]}

Taghipour, Mehrdad ^{[4
]}

Abd El-Raouf, M. M. ^{[5
]}

机构：

[1] Jouf Univ, Coll Sci, Dept Math, Sakaka, Saudi Arabia

[2] Minia Univ, Fac Sci, Dept Math, Al Minya, Egypt

[3] Higher Educ Ctr Eghlid, Dept Stat, Eghlid, Iran

[4] Univ Qom, Fac Sci, Dept Stat, Qom, Iran

[5] Arab Acad Sci Technol & Maritime Transport AASTMT, Basic & Appl Sci Inst, Alexandia, Egypt

来源：

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE | 2021年 / 2021卷

关键词：

SYSTEMS; YIELD;

D O I：

10.1155/2021/1087871

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Stress-strength models have been frequently studied in recent years. An applicable extension of these models is conditional stress-strength models. The maximum likelihood estimator of conditional stress-strength models, asymptotic distribution of this estimator, and its confidence intervals are obtained for Kumaraswamy distribution. In addition, Bayesian estimation and bootstrap method are applied to the model.

引用

页数：13

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