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Bias Reduction of MLEs for Weibull Distributions under Grouped Lifetime Data

Summary: Accelerated life tests (ALTs) usually contain subsampling because of the cost-effective evaluation. The two-stage method can deal with grouped data with subsampling, but the bias of maximum likelihood estimates (MLEs) can be alarmingly high. In this article, we propose reducing the bias of MLEs for grouped data via an unbiasing factor method. We introduce the procedures and give the unbiasing factor values. The proposed method is studied and compared with the modified maximum likelihood method for relative bias (RB) and mean square error (MSE) in Monte Carlo simulations. The results show that the unbiasing factor method is better in most cases.

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  • Topics: Engineering
  • Keywords: Censoring, Grouped data, MLEs, Unbiasing factor, Weibull distribution
  • Author: Wang, Guodong; Niu, Zhanwen; He, Zhen;
  • Journal: Quality Engineering