COMPARING PROBABILISTIC METHODS FOR OUTLIER DETECTION IN LINEAR-MODELS
COMPARING PROBABILISTIC METHODS FOR OUTLIER DETECTION IN LINEAR-MODELS
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DOI：
10.1093/biomet/80.3.603
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发表时间：
1993-09-01
期刊：
影响因子：
2.7
通讯作者：
GUTTMAN, I
中科院分区：
文献类型：
--
作者：
PENA, D;GUTTMAN, I
本文比较了两种后验概率方法处理线性模型中的异常值。我们表明，把诊断，来自均值漂移和方差漂移模型产生的程序，似乎是更有效的比使用的概率计算的后验分布的实际实现的残差。的关系，建议的程序，使用一定的预测分布的诊断推导。
This paper compares the use of two posterior probability methods to deal with outliers in linear models. We show that putting together diagnostics that come from the mean-shift and variance-shift models yields a procedure that seems to be more effective than the use of probabilities computed from the posterior distributions of actual realized residuals. The relation of the suggested procedure to the use of a certain predictive distribution for diagnostics is derived.