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An Efficient Shrinkage Estimators For Generalized Inverse Rayleigh Distribution Based On Bounded And Series Stress-Strength Models
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Abstract<p>In this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.</p>
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Publication Date
Mon Jun 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
On Bayesian Estimation of System Reliability in Stress – Strength Model Based on Generalized Inverse Rayleigh Distribution
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Abstract<p>The parameter and system reliability in stress-strength model are estimated in this paper when the system contains several parallel components that have strengths subjects to common stress in case when the stress and strengths follow Generalized Inverse Rayleigh distribution by using different Bayesian estimation methods. Monte Carlo simulation introduced to compare among the proposal methods based on the Mean squared Error criteria.</p>
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Publication Date
Sun Jan 02 2011
Journal Name
Education College Journal/al-mustansiriyah
Double Stage Shrinkage Estimators of Two Parameters Generalized Rayleigh Distribution
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Publication Date
Fri Oct 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Truncated Inverse Generalized Rayleigh Distribution and Some Properties
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Truncated distributions arise naturally in many practical situations. It’s a conditional distribution that develops when the parent distribution's domain is constrained to a smaller area. The distribution of a right truncated is one of the types of a single truncated that is restricted within a specific field and usually occurs when the specified period for the study is complete.  Hence, this paper introduces Right Truncated Inverse Generalized Rayleigh Distribution (RTIGRD) with two parameters  is introduced. Then, provided some properties such as; (probability density function, cumulative distribution function (CDF), survival function, hazard function, ‎rth moment, mean,   variance, Moment Generating Function, Skewness, kurtosi

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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimation of a Parallel Stress-strength Model Based on the Inverse Kumaraswamy Distribution
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 The reliability of the stress-strength model attracted many statisticians for several years owing to its applicability in different and diverse parts such as engineering, quality control, and economics. In this paper, the system reliability estimation in the stress-strength model containing Kth parallel components will be offered by four types of shrinkage methods: constant Shrinkage Estimation Method, Shrinkage Function Estimator, Modified Thompson Type Shrinkage Estimator, Squared Shrinkage Estimator. The Monte Carlo simulation study is compared among proposed estimators using the mean squared error. The result analyses of the shrinkage estimation methods showed that the shrinkage functions estimator was the best since

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Publication Date
Sun Mar 21 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Estimation of the reliability system in model of stress- strength according to distribution of inverse Rayleigh
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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
Estimating the Reliability Function of some Stress- Strength Models for the Generalized Inverted Kumaraswamy Distribution
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This paper discusses reliability of the stress-strength model. The reliability functions 𝑅1 and 𝑅2 were obtained for a component which has an independent strength and is exposed to two and three stresses, respectively. We used the generalized inverted Kumaraswamy distribution GIKD with unknown shape parameter as well as known shape and scale parameters. The parameters were estimated from the stress- strength models, while the reliabilities 𝑅1, 𝑅2 were estimated by three methods, namely the Maximum Likelihood,  Least Square, and Regression.

 A numerical simulation study a comparison between the three estimators by mean square error is performed. It is found that best estimator between

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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economic And Administrative Science
On Shrinkage Estimation for Generalized Exponential Distribution
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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Employ Shrinkage Estimation Technique for the Reliability System in Stress-Strength Models: special case of Exponentiated Family Distribution
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       A reliability system of the multi-component stress-strength model R(s,k) will be considered in the present paper ,when the stress and strength are independent and non-identically distribution have the Exponentiated Family Distribution(FED) with the unknown  shape parameter α and known scale parameter λ  equal to two and parameter θ equal to three. Different estimation methods of R(s,k) were introduced corresponding to Maximum likelihood and Shrinkage estimators. Comparisons among the suggested estimators were prepared depending on simulation established on mean squared error (MSE) criteria.

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Publication Date
Mon Apr 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimators of the parameter and Reliability Function of Inverse Rayleigh Distribution" A comparison study "
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     In this paper, Bayesian estimator for the parameter and reliability function of inverse Rayleigh distribution (IRD) were obtained Under three types of loss function, namely, square error loss function (SELF), Modified Square error loss function (MSELF) and Precautionary loss function (PLF),taking into consideration the  informative and non- informative  prior. The performance of such estimators was assessed on the basis of mean square error (MSE) criterion by performing a Monte Carlo simulation technique.

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Publication Date
Sun Dec 01 2019
Journal Name
2019 First International Conference Of Computer And Applied Sciences (cas)
A Comparison for Some of the estimation methods of the Parallel Stress-Strength model In the case of Inverse Rayleigh Distribution
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