Jackknife-After-Bootstrap Method for Detection of Influential Observations in Linear Regression Models

DOI10.1080/03610918.2012.661908zbMath1347.62052OpenAlexW1996861005MaRDI QIDQ4929161

Aylin Alin, Ufuk Beyaztas

Publication date: 13 June 2013

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.661908

zbMATH Keywords

bootstrapjackknifeinfluential observationlikelihood distancemodified Cook's distancet-starWelsch's distance

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Bootstrap, jackknife and other resampling methods (62F40) Nonparametric statistical resampling methods (62G09) Diagnostics, and linear inference and regression (62J20)

Related Items (4)

Identification of influential observations based on binary particle swarm optimization in the cox PH model ⋮ Robust BCa–JaB method as a diagnostic tool for linear regression models ⋮ Sufficient jackknife-after-bootstrap method for detection of influential observations in linear regression models ⋮ Jackknife-After-Bootstrap as Logistic Regression Diagnostic Tool

Uses Software

• R

Cites Work

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• Bootstrap methods: another look at the jackknife
• Detection of Influential Observation in Linear Regression
• Jackknife-after-bootstrap regression influence diagnostics

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