Analysis of generalized inverted exponential competing risks model in presence of partially observed failure modes
In reliability engineering or medical studies, failure of units or individuals may occurring due to several failure modes which is known by competing risks model. In this paper, we have adopted a competing risks model under consideration that, the failure time has generalized inverted exponential di...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
|
| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016823006038 |
| _version_ | 1797736882497388544 |
|---|---|
| author | Al-Wageh A. Farghal Souha K Badr Hanaa Abu-Zinadah Gamal A. Abd-Elmougod |
| author_facet | Al-Wageh A. Farghal Souha K Badr Hanaa Abu-Zinadah Gamal A. Abd-Elmougod |
| author_sort | Al-Wageh A. Farghal |
| collection | DOAJ |
| description | In reliability engineering or medical studies, failure of units or individuals may occurring due to several failure modes which is known by competing risks model. In this paper, we have adopted a competing risks model under consideration that, the failure time has generalized inverted exponential distribution (GIED) and the failure modes are independent and partially observed. Under type-II progressive censoring scheme (type-II PCS), the experiment is designed as a quite popular scheme for collecting data specially, for a highly reliable product. The point estimates of the model parameters are formulated under classical approach (maximum likelihood and bootstrap) and Bayesian approach with respect to the symmetric squared error loss function. Also, the approximate confidence intervals under a large sample theory, bootstrap technique’s and Markov chain Monte Carlo method (MCMC) are constructed. The estimators are assessed and compared with building the simulation study. Analysis a set of type-II PCS competing risks mortality data for illustration purpose. |
| first_indexed | 2024-03-12T13:20:38Z |
| format | Article |
| id | doaj.art-a28e1a01a624428a95cc31f67c3b1752 |
| institution | Directory Open Access Journal |
| issn | 1110-0168 |
| language | English |
| last_indexed | 2024-03-12T13:20:38Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj.art-a28e1a01a624428a95cc31f67c3b17522023-08-26T04:42:52ZengElsevierAlexandria Engineering Journal1110-01682023-09-01787487Analysis of generalized inverted exponential competing risks model in presence of partially observed failure modesAl-Wageh A. Farghal0Souha K Badr1Hanaa Abu-Zinadah2Gamal A. Abd-Elmougod3Department of Mathematics, Faculty of Science, Sohag University, Sohag 82524, EgyptDepartment of Statistics, College of Science, University of Jeddah, Jeddah, Saudi ArabiaDepartment of Statistics, College of Science, University of Jeddah, Jeddah, Saudi ArabiaDepartment of Mathematics, Faculty of Science, Damanhour University, Damanhour, Egypt; Corresponding author.In reliability engineering or medical studies, failure of units or individuals may occurring due to several failure modes which is known by competing risks model. In this paper, we have adopted a competing risks model under consideration that, the failure time has generalized inverted exponential distribution (GIED) and the failure modes are independent and partially observed. Under type-II progressive censoring scheme (type-II PCS), the experiment is designed as a quite popular scheme for collecting data specially, for a highly reliable product. The point estimates of the model parameters are formulated under classical approach (maximum likelihood and bootstrap) and Bayesian approach with respect to the symmetric squared error loss function. Also, the approximate confidence intervals under a large sample theory, bootstrap technique’s and Markov chain Monte Carlo method (MCMC) are constructed. The estimators are assessed and compared with building the simulation study. Analysis a set of type-II PCS competing risks mortality data for illustration purpose.http://www.sciencedirect.com/science/article/pii/S1110016823006038Generalized inverted exponential distributionType-II progressive censoring schemeCompeting risks modelMaximum likelihood estimationBootstrap confidence intervalBayesian estimation |
| spellingShingle | Al-Wageh A. Farghal Souha K Badr Hanaa Abu-Zinadah Gamal A. Abd-Elmougod Analysis of generalized inverted exponential competing risks model in presence of partially observed failure modes Alexandria Engineering Journal Generalized inverted exponential distribution Type-II progressive censoring scheme Competing risks model Maximum likelihood estimation Bootstrap confidence interval Bayesian estimation |
| title | Analysis of generalized inverted exponential competing risks model in presence of partially observed failure modes |
| title_full | Analysis of generalized inverted exponential competing risks model in presence of partially observed failure modes |
| title_fullStr | Analysis of generalized inverted exponential competing risks model in presence of partially observed failure modes |
| title_full_unstemmed | Analysis of generalized inverted exponential competing risks model in presence of partially observed failure modes |
| title_short | Analysis of generalized inverted exponential competing risks model in presence of partially observed failure modes |
| title_sort | analysis of generalized inverted exponential competing risks model in presence of partially observed failure modes |
| topic | Generalized inverted exponential distribution Type-II progressive censoring scheme Competing risks model Maximum likelihood estimation Bootstrap confidence interval Bayesian estimation |
| url | http://www.sciencedirect.com/science/article/pii/S1110016823006038 |
| work_keys_str_mv | AT alwagehafarghal analysisofgeneralizedinvertedexponentialcompetingrisksmodelinpresenceofpartiallyobservedfailuremodes AT souhakbadr analysisofgeneralizedinvertedexponentialcompetingrisksmodelinpresenceofpartiallyobservedfailuremodes AT hanaaabuzinadah analysisofgeneralizedinvertedexponentialcompetingrisksmodelinpresenceofpartiallyobservedfailuremodes AT gamalaabdelmougod analysisofgeneralizedinvertedexponentialcompetingrisksmodelinpresenceofpartiallyobservedfailuremodes |