Statistical analysis for masked system life data from Marshall‐Olkin Weibull distribution under progressive hybrid censoring
研究了串联系统中屏蔽数据的统计分析，假设组件寿命服从Marshall-Olkin Weibull分布，基于渐进混合删失数据推导了参数估计方法，并比较了不同估计量的表现。
Abstract This paper considers the statistical analysis of masked data in a series system, where the components are assumed to have Marshall‐Olkin Weibull distribution. Based on type‐I progressive hybrid censored and masked data, we derive the maximum likelihood estimates, approximate confidence intervals, and bootstrap confidence intervals of unknown parameters. As the maximum likelihood estimate does not exist for small sample size, Gibbs sampling is used to obtain the Bayesian estimates and Monte Carlo method is employed to construct the credible intervals based on Jefferys prior with partial information. Numerical simulations are performed to compare the performances of the proposed methods and one data set is analyzed.