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Statistical prediction of failure times under generalized progressive hybrid censoring in a simple step-stress accelerated competing risks model

Chunfang Zhang and Yimin Shi*   

  1. Department of Applied Mathematics, Northwestern Polytechnical University, Xi’an 710072, China
  • Online:2017-04-25 Published:2010-01-03

Abstract:

Based on a simple step-stress accelerated competing risks model from generalized exponential distribution, the statistical prediction problem of unobserved failure times under generalized progressive hybrid censoring is investigated. Using the cumulative exposure model, maximum likelihood predictors, conditional median predictors, approximate prediction intervals and conditional prediction intervals of model parameters and unobserved competing failure times are obtained. To support and illustrate the prediction methods, an available dataset is analyzed and a simulation study is carried out. The numerical results of predictors of model parameters and competing failure times show that the prediction methods have a good performance.