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多元数据中的异常值识别AI 解读

New insights are given into why the problem of detecting multivariate outliers can be difficult and why the difficulty increases with the dimension of the data. Significant improvements in methods for detecting outliers are described, and extensive simulation experiments demonstrate that a hybrid method extends the practical boundaries of outlier detection capabilities. Based on simulation results and examples from the literature, the question of what levels of contamination…

高维多元位置与形状 S 估计量的稳健性AI 解读

For the problem of robust estimation of multivariate location and shape, defining S-estimators using scale transformations of a fixed $\rho$ function regardless of the dimension, as is usually done, leads to a perverse outcome: estimators in high dimension can have a breakdown point approaching 50%, but still fail to reject as outliers points that are large distances from the main mass of points. This leads to a form of nonrobustness that has important practical…

利用复合估计量实现高维多元位置与形状的可计算稳健估计AI 解读

Estimation of multivariate shape and location in a fashion that is robust with respect to outliers and is affine equivariant represents a significant challenge. The use of compound estimators that use a combinatorial estimator such as Rousseeuw's minimum volume ellipsoid (MVE) or minimum covariance determinant (MCD) to find good starting points for high-efficiency robust estimators such as S estimators has been proposed. In this article we indicate why this scheme will fail…

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小样本中的异常值抗性AI 解读

This paper presents a new measure of outlier resistance based on Huber's maximum bias. After standardizing by the maximum bias of the median for the same situation, outlier resistance seems to be essentially independent of n and depends on the fraction of contamination. The advantages over alternative measures of resistance involve this relative stability with the sample size, and the ability to measure resistance to a large fraction of outliers. As an example, this method…

小样本中的异常值抵抗性AI 解读

This paper presents a new measure of outlier resistance based on Huber's maximum bias. After standardizing by the maximum bias of the median for the same situation, outlier resistance seems to be essentially independent of n and depends on the fraction of contamination. The advantages over alternative measures of resistance involve this relative stability with the sample size, and the ability to measure resistance to a large fraction of outliers. As an example, this method…

实验室间研究的稳健统计分析AI 解读

A common procedure in testing analytical methods is to send a portion of each of a number of samples to each of several laboratories. The results of such a study are submitted to statistical analysis to determine the two important variance components in the problem: replication error and laboratory bias. Outliers are relatively common in these data both among laboratory effects and among the residuals. This paper presents a method of analysis for interlaboratory studies that…

实验室间研究的稳健统计分析AI 解读

A common procedure in testing analytical methods is to send a portion of each of a number of samples to each of several laboratories. The results of such a study are submitted to statistical analysis to determine the two important variance components in the problem: replication error and laboratory bias. Outliers are relatively common in these data both among laboratory effects and among the residuals. This paper presents a method of analysis for interlaboratory studies that…