Statistical inference on accelerated life testing with dependent competing failure model under progressively type‐II censored data based on copula theory
Ying Wang, Zaizai Yan
Abstract
Abstract In this paper, we discuss the statistical analysis of a constant‐stress accelerated dependent competing failure model under progressively type‐II censoring based on a copula function. The dependence structure of lifetimes is constructed when the copula is a bivariate Clayton copula. The maximum likelihood estimations (MLEs) of the model parameters are derived. We also get the coverage probability of the 95% confidence intervals of the parameters based on MLEs and bootstrap confidence intervals. Finally, a real data set of some insulation system for electric motors was demonstrated for illustrative purpose.
Topics & Concepts
Copula (linguistics)Bivariate analysisCensoring (clinical trials)Accelerated life testingConfidence intervalStatisticsMathematicsInferenceStatistical inferenceEconometricsBivariate dataLikelihood functionMaximum likelihoodComputer scienceWeibull distributionArtificial intelligenceStatistical Distribution Estimation and ApplicationsReliability and Maintenance OptimizationProbabilistic and Robust Engineering Design