Pooling shrinkage estimator of reliability for exponential failure model using the sampling plan (n, C, T)

Al-Hemyari, Z.A.,Jehel, A.K. The Korean Reliability Society 2011 International Journal of Reliability and Applicati Vol.12 No.1

One of the most important problems in the estimation of the parameter of the failure model, is the cost of experimental sampling units, which can be reduced by using any prior information available about ${\theta}$, and devising a two-stage pooling shrunken estimation procedure. We have proposed an estimator of the reliability function (R(t)) of the exponential model using two-stage time censored data when a prior value about the unknown parameter (${\theta}$) is available from the past. To compare the performance of the proposed estimator with the classical estimator, computer intensive calculations for bias, mean squared error, relative efficiency, expected sample size and percentage of the overall sample size saved expressions, were done for varying the constants involved in the proposed estimator (${\tilde{R}}$(t)).

On simple estimation technique for the reliability of exponential lifetime model

Al-Hemyari, Z.A.,Al-Saidy, Obaid M.,Al-Ali, A.R. The Korean Reliability Society 2013 International Journal of Reliability and Applicati Vol.14 No.2

Exponential distribution plays a key role in engineering reliability and its applications. The exponential failure model has been studied for years. This article introduces two new preliminary test estimators for the reliability function (R(t)) in complete and censored samples from the exponential model with the use of a prior estimation (${\theta}_0$) of the mean (${\theta}$). The proposed preliminary test estimators are studied and compared numerically with the existing estimators. Computer-intensive calculations for bias and relative efficiency show that for, different values of levels of significance and for varying constants involved in the proposed estimators, the proposed estimators are far better than classical and existing estimators.

Computational procedures for exponential life model incorporating Bayes and shrinkage techniques

Al-Hemyari, Zuhair A.,Al-Dabag, H.A.,Al-Humairi, Ali Z. The Korean Reliability Society 2015 International Journal of Reliability and Applicati Vol.16 No.2

It is well known that using any additional information in the estimation of unknown parameters with new sample of observations diminishes the sampling units needed and minimizes the risk of new estimators. There are many rational reasons to assure that the existence of additional information in practice and there exists many practical cases in which additional information is available in the form of target value (initial value) about the unknown parameters. This article is described the problem of how the prior initial value about the unknown parameters can be utilized and combined with classical Bayes estimator to get a new combination of Bayes estimator and prior value to improve the properties of the new combination. In this article, two classes of Bayes-shrinkage and preliminary test Bayes-shrinkage estimators are proposed for the scale parameter of exponential distribution. The bias, risk and risk ratio expressions are derived and studied. The performance of the proposed classes of estimators is studied for different choices of constants engaged in the estimators. The comparisons, conclusions and recommendations are demonstrated.

Lightweight Multicast Routing Based on Stable Core for MANETs

( Abdulmalek Al-hemyari ),( Mahamod Ismail ),( Rosilah Hassan ),( Sabri Saeed ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.12

Mobile ad hoc networks (MANETs) have recently gained increased interest due to the widespread use of smart mobile devices. Group communication applications, serving for better cooperation between subsets of business members, become more significant in the context of MANETs. Multicast routing mechanisms are very useful communication techniques for such group-oriented applications. This paper deals with multicast routing problems in terms of stability and scalability, using the concept of stable core. We propose LMRSC (Lightweight Multicast Routing Based on Stable Core), a lightweight multicast routing technique for MANETs, in order to avoid periodic flooding of the source messages throughout the network, and to increase the duration of multicast routes. LMRSC establishes and maintains mesh architecture for each multicast group member by dividing the network into several zones, where each zone elects the most stable node as its core. Node residual energy and node velocity are used to calculate the node stability factor. The proposed algorithm is simulated by using NS-2 simulation, and is compared with other multicast routing mechanisms: ODMRP and PUMA. Packet delivery ratio, multicast route lifetime, and control packet overhead are used as performance metrics. These metrics are measured by gradual increase of the node mobility, the number of sources, the group size and the number of groups. The simulation performance results indicate that the proposed algorithm outperforms other mechanisms in terms of routes stability and network density.

Computational procedures for exponential life model incorporating Bayes and shrinkage techniques

Zuhair A. Al-Hemyari,H. A. Al-Dabag,Ali Z. Al-Humairi 한국신뢰성학회 2015 International Journal of Reliability and Applicati Vol.16 No.2

It is well known that using any additional information in the estimation of unknown parameters with new sample of observations diminishes the sampling units needed and minimizes the risk of new estimators. There are many rational reasons to assure that the existence of additional information in practice and there exists many practical cases in which additional information is available in the form of target value (initial value) about the unknown parameters. This article is described the problem of how the prior initial value about the unknown parameters can be utilized and combined with classical Bayes estimator to get a new combination of Bayes estimator and prior value to improve the properties of the new combination. In this article, two classes of Bayesshrinkage and preliminary test Bayes-shrinkage estimators are proposed for the scale parameter of exponential distribution. The bias, risk and risk ratio expressions are derived and studied. The performance of the proposed classes of estimators is studied for different choices of constants engaged in the estimators. The comparisons, conclusions and recommendations are demonstrated.

Pooling shrinkage estimator of reliability for exponential failure model using the sampling plan (n, C, T)

Z. A. Al-Hemyari,A. K. Jehel 한국신뢰성학회 2011 International Journal of Reliability and Applicati Vol.12 No.1

One of the most important problems in the estimation of the parameter of the failure model, is the cost of experimental sampling units, which can be reduced by using any prior information available about θ , and devising a two-stage pooling shrunken estimation procedure. We have proposed an estimator of the reliability function ( R(t) ) of the exponential model using two-stage time censored data when a prior value about the unknown parameter (θ ) is available from the past. To compare the performance of the proposed estimator with the classical estimator, computer intensive calculations for bias, mean squared error, relative efficiency, expected sample size and percentage of the overall sample size saved expressions, were done for varying the constants involved in the proposed estimator ( R (t) ).

On simple estimation technique for the reliability of exponential lifetime model

Z. A. Al-Hemyari,Obaid M. Al-Saidy,A. R. Al-Ali 한국신뢰성학회 2013 International Journal of Reliability and Applicati Vol.14 No.2

Exponential distribution plays a key role in engineering reliability and its applications. The exponential failure model has been studied for years. This article introduces two new preliminary test estimators for the reliability function ( R(t) ) in complete and censored samples from the exponential model with the use of a prior estimation ( θ0 ) of the mean ( θ ) . The proposed preliminary test estimators are studied and compared numerically with the existing estimators. Computer-intensive calculations for bias and relative efficiency show that for, different values of levels of significance and for varying constants involved in the proposed estimators, the proposed estimators are far better than classical and existing estimators.