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E- Bayesian Estimation of System Reliability (Series, Parallel) and Failure Rate Functions with Kumaraswamy Distribution based on Type II Censoring Data

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@article{IJASEIT12636,
   author = {Wafaa J. Hussain and Ahmed A. Akka and Rehab K. Hamza},
   title = {E- Bayesian Estimation of System Reliability (Series, Parallel) and Failure Rate Functions with Kumaraswamy Distribution based on  Type II Censoring Data},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {10},
   number = {4},
   year = {2020},
   pages = {1477--1482},
   keywords = {bayesian estimation; system reliability; kumaraswamy distribution; censoring data; MAPE.},
   abstract = {

In this paper, the failure rate function and the shape parameter for the kumaraswamy distribution and reliability function of a system with a number (m) of independent compounds associated with a system (serial, parallel) were estimated, by relying on observational data of the second type, knowing that the survival time of the compounds are independent. Based on the findings the graphical predictor of the failure rate and parameter - and the reliability function of the serial and parallel system is smaller than the Standard Bayesian estimator (MLE) in simulation and real data. Thus, a decreasing in AMPE with an increase in the sample size n and an increase in the size of the failure sample r as the physical prediction capabilities have a high efficiency. The using of the Bayesian prediction method to estimate the reliability of different production systems for other failure distributions such as the Burr family distributions and various other failure distributions. Based on the output he results are reasonably consistent with simulation and real data. The E-Bayesian method was used for estimating with three primary distribution functions for the above parameters and comparing them with the standard Bayesian method with a squared loss function and the maximum likelihood method where simulation experiments were employed to compare the estimation results and the results showed the advantage of the E-Bayesian method in estimating through comparison statistics (MAPE).

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12636},    doi = {10.18517/ijaseit.10.4.12636} }

EndNote

%A Hussain, Wafaa J.
%A Akka, Ahmed A.
%A Hamza, Rehab K.
%D 2020
%T E- Bayesian Estimation of System Reliability (Series, Parallel) and Failure Rate Functions with Kumaraswamy Distribution based on  Type II Censoring Data
%B 2020
%9 bayesian estimation; system reliability; kumaraswamy distribution; censoring data; MAPE.
%! E- Bayesian Estimation of System Reliability (Series, Parallel) and Failure Rate Functions with Kumaraswamy Distribution based on  Type II Censoring Data
%K bayesian estimation; system reliability; kumaraswamy distribution; censoring data; MAPE.
%X 

In this paper, the failure rate function and the shape parameter for the kumaraswamy distribution and reliability function of a system with a number (m) of independent compounds associated with a system (serial, parallel) were estimated, by relying on observational data of the second type, knowing that the survival time of the compounds are independent. Based on the findings the graphical predictor of the failure rate and parameter - and the reliability function of the serial and parallel system is smaller than the Standard Bayesian estimator (MLE) in simulation and real data. Thus, a decreasing in AMPE with an increase in the sample size n and an increase in the size of the failure sample r as the physical prediction capabilities have a high efficiency. The using of the Bayesian prediction method to estimate the reliability of different production systems for other failure distributions such as the Burr family distributions and various other failure distributions. Based on the output he results are reasonably consistent with simulation and real data. The E-Bayesian method was used for estimating with three primary distribution functions for the above parameters and comparing them with the standard Bayesian method with a squared loss function and the maximum likelihood method where simulation experiments were employed to compare the estimation results and the results showed the advantage of the E-Bayesian method in estimating through comparison statistics (MAPE).

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12636 %R doi:10.18517/ijaseit.10.4.12636 %J International Journal on Advanced Science, Engineering and Information Technology %V 10 %N 4 %@ 2088-5334

IEEE

Wafaa J. Hussain,Ahmed A. Akka and Rehab K. Hamza,"E- Bayesian Estimation of System Reliability (Series, Parallel) and Failure Rate Functions with Kumaraswamy Distribution based on  Type II Censoring Data," International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 4, pp. 1477-1482, 2020. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.10.4.12636.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Hussain, Wafaa J.
AU  - Akka, Ahmed A.
AU  - Hamza, Rehab K.
PY  - 2020
TI  - E- Bayesian Estimation of System Reliability (Series, Parallel) and Failure Rate Functions with Kumaraswamy Distribution based on  Type II Censoring Data
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 10 (2020) No. 4
Y2  - 2020
SP  - 1477
EP  - 1482
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - bayesian estimation; system reliability; kumaraswamy distribution; censoring data; MAPE.
N2  - 

In this paper, the failure rate function and the shape parameter for the kumaraswamy distribution and reliability function of a system with a number (m) of independent compounds associated with a system (serial, parallel) were estimated, by relying on observational data of the second type, knowing that the survival time of the compounds are independent. Based on the findings the graphical predictor of the failure rate and parameter - and the reliability function of the serial and parallel system is smaller than the Standard Bayesian estimator (MLE) in simulation and real data. Thus, a decreasing in AMPE with an increase in the sample size n and an increase in the size of the failure sample r as the physical prediction capabilities have a high efficiency. The using of the Bayesian prediction method to estimate the reliability of different production systems for other failure distributions such as the Burr family distributions and various other failure distributions. Based on the output he results are reasonably consistent with simulation and real data. The E-Bayesian method was used for estimating with three primary distribution functions for the above parameters and comparing them with the standard Bayesian method with a squared loss function and the maximum likelihood method where simulation experiments were employed to compare the estimation results and the results showed the advantage of the E-Bayesian method in estimating through comparison statistics (MAPE).

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12636 DO - 10.18517/ijaseit.10.4.12636

RefWorks

RT Journal Article
ID 12636
A1 Hussain, Wafaa J.
A1 Akka, Ahmed A.
A1 Hamza, Rehab K.
T1 E- Bayesian Estimation of System Reliability (Series, Parallel) and Failure Rate Functions with Kumaraswamy Distribution based on  Type II Censoring Data
JF International Journal on Advanced Science, Engineering and Information Technology
VO 10
IS 4
YR 2020
SP 1477
OP 1482
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 bayesian estimation; system reliability; kumaraswamy distribution; censoring data; MAPE.
AB 

In this paper, the failure rate function and the shape parameter for the kumaraswamy distribution and reliability function of a system with a number (m) of independent compounds associated with a system (serial, parallel) were estimated, by relying on observational data of the second type, knowing that the survival time of the compounds are independent. Based on the findings the graphical predictor of the failure rate and parameter - and the reliability function of the serial and parallel system is smaller than the Standard Bayesian estimator (MLE) in simulation and real data. Thus, a decreasing in AMPE with an increase in the sample size n and an increase in the size of the failure sample r as the physical prediction capabilities have a high efficiency. The using of the Bayesian prediction method to estimate the reliability of different production systems for other failure distributions such as the Burr family distributions and various other failure distributions. Based on the output he results are reasonably consistent with simulation and real data. The E-Bayesian method was used for estimating with three primary distribution functions for the above parameters and comparing them with the standard Bayesian method with a squared loss function and the maximum likelihood method where simulation experiments were employed to compare the estimation results and the results showed the advantage of the E-Bayesian method in estimating through comparison statistics (MAPE).

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12636 DO - 10.18517/ijaseit.10.4.12636