Influence Diagnostics for a Class of Biased Estimators in Regression

  • Esteban Walker
Conference paper


Fractional Principal Components (FPC) is a large class of estimators that include, among others, least squares (LS), ridge, principal components, fractional rank, and Stein estimators. This paper addresses the measurement of influence for FPC estimators. It is shown that the residual and the leverage of any observation depends directly on the “fraction” of the principal components that is used. Generalizations of popular measures of influence for LS are proposed. Approximate deletion formulas are presented.


Ridge Regression Principal Component Regression Little Square Estimator Popular Measure Influence Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York, Inc. 1992

Authors and Affiliations

  • Esteban Walker
    • 1
  1. 1.Dept. of StatisticsU. of TennesseeKnoxvilleUSA

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