Sufficient jackknife-after-bootstrap method for detection of influential observations in linear regression models

DOI10.1007/s00362-013-0548-4zbMath1306.62081OpenAlexW2060574170MaRDI QIDQ465626

Ufuk Beyaztas, Aylin Alin

Publication date: 24 October 2014

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-013-0548-4

zbMATH Keywords

bootstrapregression diagnosticsinfluential observationjacknifesufficient bootstrap

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Bootstrap, jackknife and other resampling methods (62F40)

Related Items (2)

Sufficient m-out-of-n (m/n) bootstrap ⋮ Unnamed Item

Cites Work

• Influence diagnostics in the varying coefficient model with longitudinal data
• Sufficient bootstrapping
• Influential observations, high leverage points, and outliers in linear regression
• Influence diagnostics for the Grubbs's model
• Characterizations of an Empirical Influence Function for Detecting Influential Cases in Regression
• Detection of Influential Observation in Linear Regression
• Influential Observations in Linear Regression
• Jackknife-After-Bootstrap Method for Detection of Influential Observations in Linear Regression Models
• Jackknife-after-bootstrap regression influence diagnostics
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