We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Statistical inference for constant‐stress accelerated life tests with dependent competing risks from Marshall‐Olkin bivariate exponential distribution.
- Authors
Bai, Xuchao; Shi, Yimin; Liu, Yiming; Zhang, Chunfang
- Abstract
This paper considers a constant‐stress accelerated dependent competing risks model under Type‐II censoring. The dependent structure between competing risks is modeled by a Marshall‐Olkin bivariate exponential distribution, and the accelerated model is described by the power rule model. The point and interval estimation of the model parameters and the reliability function under the normal usage condition at mission time are obtained by using the maximum likelihood estimation method and the bootstrap sampling technique. Moreover, the pivotal quantities based estimation are adopted to estimate the model parameters and the generalized confidence intervals. As a comparison, we also consider the Bayes estimation and the highest posterior density credible intervals for the model parameters based on conjugate priors and importance sampling method, respectively. To illustrate the proposed methodology, a Monte Carlo simulation is used to study the performances of different estimation methods. Finally, a dataset is analyzed for illustrative purpose and a comparison with the original results is also given.
- Subjects
ACCELERATED life testing; INFERENTIAL statistics; COMPETING risks; MONTE Carlo method; BAYES' estimation; CENSORING (Statistics); BAYESIAN analysis
- Publication
Quality & Reliability Engineering International, 2020, Vol 36, Issue 2, p511
- ISSN
0748-8017
- Publication type
Article
- DOI
10.1002/qre.2582