微粒
发表于 2025-3-23 10:04:37
General Approaches to Stepwise Identification of Unusual Values in Data Analysis, directly (via some detection procedure). This paper summarizes the backwards-stepping approach to the detection of unusual values in a data set. This approach has the advantages of simplicity of application, flexibility, and resistance to masking effects. Application to univariate, multivariate, an
压迫
发表于 2025-3-23 17:48:09
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严重伤害
发表于 2025-3-23 18:11:45
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enumaerate
发表于 2025-3-24 01:35:36
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笨重
发表于 2025-3-24 05:21:05
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蔑视
发表于 2025-3-24 07:42:09
Adaptive Efficient Weighted Least Squares With Dependent Observations,atrix of the ordinary least squares (OLS) estimator for the parameters of the linear regression model despite the possible presence of heteroskedasticity of unknown form. In this sense, such covariance matrix estimators are “robust” to unequal scale of the regression errors. Cragg proposed pa
Ige326
发表于 2025-3-24 11:55:04
Regression Quantile Diagnostics for Multiple Outliers, it is shown that the “least median of squares” estimator is . an elemental solutions (i.e., fit exactly by . observations), but is determined to have exactly . + 1) equal residuals when there are . parameters.
overhaul
发表于 2025-3-24 15:00:43
Robust Testing of Functionals,ity, however, degenerates to some kind of unbiasedness since all other “estimator tests” .(.) with . ≠ . achieve asymptotic minimum power zero..The selection of the functional .(.) to be tested leads to nontrivial optimality problems. In the one dimensional, onesided case,.one may want to test ε-con
鉴赏家
发表于 2025-3-24 22:54:04
Consumer Datesware,on sense and the fact that not all initial analysis should be robust. It seems possible that the frequent use and poor understanding of regression may make it the easiest place for robust techniques (adequately enhanced by graphical diagnosis and procedures to help choose expressions) to penetrate d
变形
发表于 2025-3-25 01:31:58
0940-6573 e the required inferences. If, how ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers.978-1-4612-8772-8978-1-4612-4444-8Series ISSN 0940-6573 Series E-ISSN 2198-3224