Accuracy of Multiple Outlier Tests in Nonlinear Regression
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초록

The original Bates-Watts framework applies only to the complete parameter vector. Thus, guidelines developed in that framework can be misleading when the adequacy of the linear approximation is very different for different subsets. The subset curvature measures appear to be reliable indicators of the adequacy of linear approximation for an arbitrary subset of parameters in nonlinear models. Given the specific mean shift outlier model, the standard approaches to obtaining test statistics for outliers are discussed. The accuracy of outlier tests is investigated using subset curvatures.

키워드

Curvature measuresintrinsic curvatureoutlier testparameter-effects curvaturesubset curvatures
제목
Accuracy of Multiple Outlier Tests in Nonlinear Regression
저자
강명욱
발행일
2011-01
저널명
Communications for Statistical Applications and Methods
18
1
페이지
131 ~ 136