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Detection of analytical bias

机译:检测分析偏差

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The main object of this paper is to consider maximum likelihood estimators for models used in detection of analytical bias. We consider the regression model proposed in Ripley and Thompson (Analyst, 112, 1987, p. 377) with an EM-type algorithm for computing maximum likelihood estimators and obtain consistent estimators for the asymptotic variance of the maximum likelihood estimators, which seems not to be available in the literature. Wald type statistics are proposed for testing hypothesis related to the bias of the analytical methods with the asymptotic chi-square distribution which guarantees correct asymptotic significance levels. The main conclusion is that proposed approaches in the literature underestimate the covariance matrix of the maximum likelihood estimators. Results of simulation studies and applications to real data sets are reported to illustrate comparisons with other approaches. [References: 11]
机译:本文的主要目的是考虑用于分析偏差检测的模型的最大似然估计。我们考虑了Ripley和Thompson(Analyst,112,1987,p.377)中提出的回归模型,该模型具有用于计算最大似然估计量的EM类型算法,并获得了最大似然估计量的渐近方差的一致估计量,这似乎并非在文献中可用。提出了Wald型统计量来检验与具有渐近卡方分布的分析方法的偏倚有关的假设,以保证正确的渐近显着性水平。主要结论是,文献中提出的方法低估了最大似然估计量的协方差矩阵。报告了模拟研究的结果以及对真实数据集的应用,以说明与其他方法的比较。 [参考:11]

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