The reliability inference for multicomponent stress–strength model under the Burr X distribution

Show simple item record

dc.contributor.author Lio, Yuhlong
dc.contributor.author Chen, Ding-Geng (Din)
dc.contributor.author Tsai, Tzong-Ru
dc.contributor.author Wang, Liang
dc.date.accessioned 2024-08-14T12:13:30Z
dc.date.available 2024-08-14T12:13:30Z
dc.date.issued 2024-03
dc.description DATA AVAILABILITY STATEMENT: Complete monthly water capacity data for the Shasta Reservoir from 1981 to 1985 are given in Appendix G. Section 6 includes the observed complete strength and stress data sets. en_US
dc.description.abstract The reliability of the multicomponent stress–strength system was investigated under the two-parameter Burr X distribution model. Based on the structure of the system, the type II censored sample of strength and random sample of stress were obtained for the study. The maximum likelihood estimators were established by utilizing the type II censored Burr X distributed strength and complete random stress data sets collected from the multicomponent system. Two related approximate confidence intervals were achieved by utilizing the delta method under the asymptotic normal distribution theory and parametric bootstrap procedure. Meanwhile, point and confidence interval estimators based on alternative generalized pivotal quantities were derived. Furthermore, a likelihood ratio test to infer the equality of both scalar parameters is provided. Finally, a practical example is provided for illustration. en_US
dc.description.department Statistics en_US
dc.description.sdg SDG-04:Quality Education en_US
dc.description.sdg SDG-09: Industry, innovation and infrastructure en_US
dc.description.sponsorship The National Science and Technology Council, the National Natural Science Foundation of China, the Yunnan Fundamental Research Projects, the Yunnan Key Laboratory of Modern Analytical Mathematics and Applications, the South Africa National Research Foundation and South Africa Medical Research Council. en_US
dc.description.uri https://www.mdpi.com/journal/appliedmath en_US
dc.identifier.citation Lio, Y.; Chen, D.-G.; Tsai, T.-R.; Wang, L. The Reliability Inference for Multicomponent Stress–Strength Model under the Burr X Distribution. AppliedMath 2024, 4, 394–426. https://doi.org/10.3390/appliedmath4010021. en_US
dc.identifier.issn 2673-9909 (online)
dc.identifier.other 10.3390/appliedmath4010021
dc.identifier.uri http://hdl.handle.net/2263/97640
dc.language.iso en en_US
dc.publisher MDPI en_US
dc.rights © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). en_US
dc.subject Multicomponent stress–strength model en_US
dc.subject Burr X distribution en_US
dc.subject Generalized pivotal estimation en_US
dc.subject Asymptotic theory en_US
dc.subject Maximum likelihood estimator (MLE) en_US
dc.subject SDG-04: Quality education en_US
dc.subject SDG-09: Industry, innovation and infrastructure en_US
dc.title The reliability inference for multicomponent stress–strength model under the Burr X distribution en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record