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部分因子实验中删失数据的贝叶斯分析AI 解读

Censored data arise naturally in industrial experiments whose observations are failure times or measurements with mixed continuous-categorical outcomes. When censored data are observed from a fractionated experiment, likelihood-based estimates quite often do not exist, especially when the opportunity for improvement is great. To circumvent this problem, we propose a Bayesian analysis strategy that has a straightforward implementation using the data augmentation and Monte…

区间删失数据线性回归模型中最大似然估计存在性的一个注记AI 解读

SUMMARY For a class of linear regression models with interval-censored data, including the exponential regression model as a special case, a necessary and sufficient condition is given for the existence of the maximum likelihood estimator (MLE). The condition is especially simple to check for simple linear regression. This result is useful for comparing the small sample properties of MLEs from different special cases of interval-censored data.