On two methods of identifying influential sets of observations

DOI10.1016/0167-7152(88)90057-0zbMath0665.62067OpenAlexW2056369799MaRDI QIDQ1116238

Subir Ghosh

Publication date: 1988

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-7152(88)90057-0

zbMATH Keywords

predictionrobustnessfittinglinear modelsCook's measureinfluential sets of observationsunavailable observations

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Factorial statistical designs (62K15)

Related Items (8)

Information complexity criteria for detecting influential observations in dynamic multivariate linear models using the genetic algorithm ⋮ A unifying representation of some case-deletion influence measures in univariate and multivariate linear regression ⋮ Factorial and response surface designs robust to missing observations ⋮ Deletion, augmentation and principal predictors ⋮ Efficiency comparisons in linear inference ⋮ Measuring influence of observations in predict1on and estimation for central composite designs ⋮ Leverage and subset efficiencies in regression ⋮ Properties of selected subset diagnostics in regression

Cites Work

• Influential observations, high leverage points, and outliers in linear regression
• Characterizations of an Empirical Influence Function for Detecting Influential Cases in Regression
• Influential Observations and Outliers in Regression
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