An evaluation of bootstrap methods for outlier detection in least squares regression

DOI10.1080/02664760600708863zbMath1118.62317OpenAlexW2013091931MaRDI QIDQ3592611

Steven Roberts, Michael A. Martin

Publication date: 13 September 2007

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664760600708863

zbMATH Keywords

error distributionjackknife-after-bootstrapcase-based resamplingexternally studentized residualsinternally studentized residualsresidual-based resamplingRSTUDENT

Mathematics Subject Classification ID

Robustness and adaptive procedures (parametric inference) (62F35) Bootstrap, jackknife and other resampling methods (62F40)

Related Items

Jackknife-after-bootstrap regression influence diagnostics ⋮ DELETE-2 AND DELETE-3 JACKKNIFE PROCEDURES FOR UNMASKING IN REGRESSION ⋮ Nonparametric tests for detection of high dimensional outliers

Uses Software

• alr3

Cites Work

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• Masking unmasked