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Majid Asadi - One of the best experts on this subject based on the ideXlab platform.
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on the mean Residual Life Function of coherent systems
IEEE Transactions on Reliability, 2008Co-Authors: Majid Asadi, S GoliforushaniAbstract:We consider a coherent structure consisting of n components having the property that if it is known that at most r components (r < n) have failed, the system is still operating with probability 1. Some examples of the systems having this property are (n - k + 1)-out-of- n, some parallel-series, and some series-parallel structures. Depending on the structure, and the number of active components of the coherent systems at time t , the mean Residual Life Function of the system is studied, by several authors. This paper investigates more properties of the mean Residual Life Function of the coherent systems sharing the described property. We will show that, when the components of the system have increasing failure rate, the mean Residual Life Function of the system is decreasing in time. Several examples, and illustrative graphs are also provided.
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the mean Residual Life Function of a k out of n structure at the system level
IEEE Transactions on Reliability, 2006Co-Authors: Majid Asadi, Ismihan BayramogluAbstract:In the study of the reliability of technical systems, k-out-of-n systems play an important role. In the present paper, we consider a k-out-of-n system consisting of n identical components with independent Lifetimes having a common distribution Function F. Under the condition that, at time t, all the components of the system are working, we propose a new definition for the mean Residual Life (MRL) Function of the system, and obtain several properties of that system.
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a note on the mean Residual Life Function of a parallel system
Communications in Statistics-theory and Methods, 2005Co-Authors: Majid Asadi, Ismihan BayramogluAbstract:Abstract One of the most important types of system structures is the parallel structure. In the present article, we propose a definition for the mean Residual Life Function of a parallel system and obtain some of its properties. The proposed definition measures the mean Residual Life Function of a parallel system consisting of n identical and independent components under the condition that n - i, i = 0, 2, …, n - 1, components of the system are working and other components of the system have already failed. It is shown that, for the case where the components of the system have increasing hazard rate, the mean Residual Life Function of the system is a nonincreasing Function of time. Finally, we will obtain an upper bound for the proposed mean Residual Life Function.
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survival analysis and reliability a note on the mean Residual Life Function of a parallel system
2005Co-Authors: Majid Asadi, Ismihan BayramogluAbstract:One of the most important types of system structures is the parallel structure. In the present article, we propose a definition for the mean Residual Life Function of a parallel system and obtain some of its properties. The proposed definition measures the mean Residual Life Function of a parallel system consisting of n identical and independent components under the condition that n− i, i = 0 2 n− 1, components of the system are working and other components of the system have already failed. It is shown that, for the case where the components of the system have increasing hazard rate, the mean Residual Life Function of the system is a nonincreasing Function of time. Finally, we will obtain an upper bound for the proposed mean Residual Life Function.
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Residual entropy and its characterizations in terms of hazard Function and mean Residual Life Function
Statistics & Probability Letters, 2000Co-Authors: Majid Asadi, Nader EbrahimiAbstract:A direct approach to measure uncertainty in the Residual Life time distribution has been initiated by Ebrahimi (1996, Sankhya Ser. A 58, 48-57) and explored further by Ebrahimi and Pellerey (1995) and Ebrahimi and Kirmani (1996). In this paper, some new properties of the proposed measure in connection to order statistics and record values are derived. The generalized Pareto distribution has been widely used in the literature. We have also given several characterizations of this distribution in terms of the proposed measure.
Mu Zhao - One of the best experts on this subject based on the ideXlab platform.
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estimation of percentile Residual Life Function with left truncated and right censored data
Communications in Statistics-theory and Methods, 2017Co-Authors: Mu Zhao, Hongmei Jiang, Yong ZhouAbstract:ABSTRACTThis article focuses on the estimation of percentile Residual Life Function with left-truncated and right-censored data. Asymptotic normality and a pointwise confidence interval that does not require estimating the unknown underlying distribution Function of the proposed empirical estimator are obtained. Some simulation studies and a real data example are used to illustrate our results.
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berry esseen bounds for the percentile Residual Life Function estimators
Statistics & Probability Letters, 2015Co-Authors: Mu Zhao, Hongmei JiangAbstract:Abstract The Berry–Esseen bounds for two estimators of the percentile Residual Life Function are established. The bound for the kernel estimator is shown sharper than in the previous work. The obtained bounds are applied to study the relative deficiency of the proposed estimators.
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a note on estimation of the mean Residual Life Function with left truncated and right censored data
Statistics & Probability Letters, 2013Co-Authors: Mu Zhao, Hongmei Jiang, Xu LiuAbstract:Abstract This note focuses on estimating the mean Residual Life Function with left-truncated and right-censored data. We show that the proposed estimator converges weakly to a Gaussian process. The performances of the estimator and its pointwise confidence intervals are illustrated through simulation studies.
Ismihan Bayramoglu - One of the best experts on this subject based on the ideXlab platform.
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the mean Residual Life Function of a k out of n structure at the system level
IEEE Transactions on Reliability, 2006Co-Authors: Majid Asadi, Ismihan BayramogluAbstract:In the study of the reliability of technical systems, k-out-of-n systems play an important role. In the present paper, we consider a k-out-of-n system consisting of n identical components with independent Lifetimes having a common distribution Function F. Under the condition that, at time t, all the components of the system are working, we propose a new definition for the mean Residual Life (MRL) Function of the system, and obtain several properties of that system.
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a note on the mean Residual Life Function of a parallel system
Communications in Statistics-theory and Methods, 2005Co-Authors: Majid Asadi, Ismihan BayramogluAbstract:Abstract One of the most important types of system structures is the parallel structure. In the present article, we propose a definition for the mean Residual Life Function of a parallel system and obtain some of its properties. The proposed definition measures the mean Residual Life Function of a parallel system consisting of n identical and independent components under the condition that n - i, i = 0, 2, …, n - 1, components of the system are working and other components of the system have already failed. It is shown that, for the case where the components of the system have increasing hazard rate, the mean Residual Life Function of the system is a nonincreasing Function of time. Finally, we will obtain an upper bound for the proposed mean Residual Life Function.
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survival analysis and reliability a note on the mean Residual Life Function of a parallel system
2005Co-Authors: Majid Asadi, Ismihan BayramogluAbstract:One of the most important types of system structures is the parallel structure. In the present article, we propose a definition for the mean Residual Life Function of a parallel system and obtain some of its properties. The proposed definition measures the mean Residual Life Function of a parallel system consisting of n identical and independent components under the condition that n− i, i = 0 2 n− 1, components of the system are working and other components of the system have already failed. It is shown that, for the case where the components of the system have increasing hazard rate, the mean Residual Life Function of the system is a nonincreasing Function of time. Finally, we will obtain an upper bound for the proposed mean Residual Life Function.
G Mohtashami R Borzadaran - One of the best experts on this subject based on the ideXlab platform.
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some results on upper bounds for the variance of Functions of the Residual Life random variables
Journal of Computational and Applied Mathematics, 2017Co-Authors: Faranak Goodarzi, Mohammad Amini, G Mohtashami R BorzadaranAbstract:As a measure of maximum dispersion from the mean, upper bounds on variance have applications in all areas of theoretical and applied mathematical sciences. In this paper, we obtain an upper bound for the variance of a Function of the Residual Life random variable Xt. Since one of the most important types of system structures is the parallel structure, we give an upper bound for the variance of a Function of this system consisting of n identical and independent components, under the condition that, at time t, nr+1, r=1,,n of its components are still working. Here we characterize the Pareto distribution through Cauchys Functional equation for mean Residual Life. It is shown that the underlying distribution Function F can be recovered from the proposed mean and variance Residual Life Function of the system for r=1. Moreover, we see that the variance Residual Lifetime of the components of the system is not necessarily a decreasing Function of r and increasing of n for r=1, unlike their mean Residual Lifetime. As an application, the variance of XF1(p0) for all p0[0,1) is investigated and also a real data analysis is presented.
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reversed variance Residual Life Function and its properties in discrete Lifetime models
International Journal of Quality & Reliability Management, 2013Co-Authors: M Khorashadizadeh, A Rezaei H Roknabadi, G Mohtashami R BorzadaranAbstract:Purpose – In reliability studies, interests in discrete failure data came relatively late in comparison to its continuous analogue. Also, discrete failure data arise in several common situations. So, in this paper the authors try to study some reliability concepts such as reversed variance and reversed mean Residual Life Functions based on discrete Lifetime random variable.Design/methodology/approach – Supposed T be a non‐negative discrete random variable, then based on reversed Residual random variable Tk*=(k−T|T≤k), some useful and applicable relations and bounds are achieved.Findings – In this paper, the authors study the reversed variance Residual Life in discrete Lifetime distributions, the results of which are not similar to the continuous case. Its relationship with reversed mean Residual Life and reversed Residual coefficient of variation are obtained. Also, its monotonicity and the associated ageing classes of distributions are discussed. Some characterization results of the class of increasing r...
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variance Residual Life Function based on double truncation
Metron-International Journal of Statistics, 2013Co-Authors: M Khorashadizadeh, A Rezaei H Roknabadi, G Mohtashami R BorzadaranAbstract:Since, most of the real observations in industrial and reliability studies, are left, right or doubly truncated data, studying the reliability concepts of the components of a system or a device based on conditional random variables, are important and usual. One of the important and applicable reliability concepts, that recently has gathered the attention of the researchers, is the variance Residual Life. In this paper, we try to study some of the reliability properties of the variance Residual Life based on doubly truncated data. Its monotonicity properties and relations with doubly truncated mean Residual Life and doubly truncated Residual coefficient of variation are discussed. Furthermore, the lower (upper) bound for it under some conditions is obtained. We also discuss and find the similar results for discrete random ageing which its differences with the continuous case, are noticeable. Finally, some examples due to this subject are mentioned.
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variance Residual Life Function in discrete random ageing
Metron-International Journal of Statistics, 2010Co-Authors: M Khorashadizadeh, A Rezaei H Roknabadi, G Mohtashami R BorzadaranAbstract:The random variable X t = X − t¦X ≥ t, which is called the Residual Life random variable, has gathered the attention of most researchers in reliability. The mean and the variance of this variable in continuous distribution have been studied by several authors. But, in discrete case, only in recent years, some studies have been done for the mean of this variable. In this paper, we define and study the properties of variance of T k = T − k¦T ≥ k where T is a discrete random variable. Besides similar results for discrete and continuous Lifetime distributions, relationships with its mean, monotonicity and the associated ageing classes of distributions are obtained for discrete cases. Furthermore, some characterization results about the class of increasing (decreasing) variance Residual Life distributions based on mean Residual Life and Residual coefficient of variation, are presented and the lower and upper bound for them are achieved.
S Goliforushani - One of the best experts on this subject based on the ideXlab platform.
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on the mean Residual Life Function of coherent systems
IEEE Transactions on Reliability, 2008Co-Authors: Majid Asadi, S GoliforushaniAbstract:We consider a coherent structure consisting of n components having the property that if it is known that at most r components (r < n) have failed, the system is still operating with probability 1. Some examples of the systems having this property are (n - k + 1)-out-of- n, some parallel-series, and some series-parallel structures. Depending on the structure, and the number of active components of the coherent systems at time t , the mean Residual Life Function of the system is studied, by several authors. This paper investigates more properties of the mean Residual Life Function of the coherent systems sharing the described property. We will show that, when the components of the system have increasing failure rate, the mean Residual Life Function of the system is decreasing in time. Several examples, and illustrative graphs are also provided.