Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)

In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood,...

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Main Authors: Sairan Hamza Raheem, Bayda Atiya Kalaf, Abbas Najim Salman
Format: Article
Language:English
Published: University of Baghdad, College of Science for Women 2021-06-01
Series:مجلة بغداد للعلوم
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Online Access:https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/4857
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author Sairan Hamza Raheem
Bayda Atiya Kalaf
Abbas Najim Salman
author_facet Sairan Hamza Raheem
Bayda Atiya Kalaf
Abbas Najim Salman
author_sort Sairan Hamza Raheem
collection DOAJ
description In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.
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institution Kabale University
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language English
publishDate 2021-06-01
publisher University of Baghdad, College of Science for Women
record_format Article
series مجلة بغداد للعلوم
spelling doaj-art-94b92c633a2f4945ae481cb3f43aae542025-08-20T03:34:52ZengUniversity of Baghdad, College of Science for Womenمجلة بغداد للعلوم2078-86652411-79862021-06-01182(Suppl.)10.21123/bsj.2021.18.2(Suppl.).1103Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)Sairan Hamza Raheem0Bayda Atiya Kalaf 1Abbas Najim Salman2IT Department, College of Computing and Information Technology, University of Garmian.Mathematics Department, College of Education (Ibn Al – Haitham), University of Baghdad, Baghdad, Iraq.Mathematics Department, College of Education (Ibn Al – Haitham), University of Baghdad, Baghdad, Iraq.In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/4857Stress-Strength Model, Inverse Rayleigh Distribution, Least Square Estimator, Maximum Likelihood Method Estimator, Moment method, Uniformly Minimum Variance Unbiased Method, Shrinkage Methods.
spellingShingle Sairan Hamza Raheem
Bayda Atiya Kalaf
Abbas Najim Salman
Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)
مجلة بغداد للعلوم
Stress-Strength Model, Inverse Rayleigh Distribution, Least Square Estimator, Maximum Likelihood Method Estimator, Moment method, Uniformly Minimum Variance Unbiased Method, Shrinkage Methods.
title Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)
title_full Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)
title_fullStr Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)
title_full_unstemmed Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)
title_short Comparison of Some of Estimation methods of Stress-Strength Model: R = P(Y < X < Z)
title_sort comparison of some of estimation methods of stress strength model r p y x z
topic Stress-Strength Model, Inverse Rayleigh Distribution, Least Square Estimator, Maximum Likelihood Method Estimator, Moment method, Uniformly Minimum Variance Unbiased Method, Shrinkage Methods.
url https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/4857
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