Comparison of the Stein and the usual estimators for the regression error variance under the Pitman nearness criterion when variables are omitted

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

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Detail(s)

Original languageEnglish
Pages (from-to)151-160
Journal / PublicationStatistical Papers
Volume50
Issue number1
Publication statusPublished - Jan 2009

Abstract

This paper compares the Stein and the usual estimators of the error variance under the Pitman nearness (PN) criterion in a regression model which is mis-specified due to missing relevant explanatory variables. The exact expression of the PN-probability is derived and numerically evaluated. Contrary to the well-known result under mean squared errors (MSE), with the PN criterion the Stein variance estimator is uniformly dominated by the usual estimator when no relevant variables are excluded from the model. With an increased degree of model mis-specification, neither estimator strictly dominates the other. © 2007 Springer-Verlag.

Research Area(s)

  • Omitted variables, Pitman nearness, Stein variance estimator