A note on asymmetry and robustness in linear regression /

Bibliographic Details
Main Authors:	Carroll, Raymond J. (Author), Welsh, A. H. (Alan H.), 1960- (Author)
Corporate Author:	United States. Air Force. Office of Scientific Research (sponsoring body.)
Format:	Book
Language:	English
Published:	College Station, Texas : Department of Statistics, Texas A & M University, [1987]
Series:	Technical report (Texas A & M University. Department of Statistics) ; no. 13.
Subjects:	Regression analysis. Robust statistics. Error analysis (Mathematics) Symmetry (Mathematics) Estimation theory > Asymptotic theory. Mathematical statistics. Estimating equations Bounded influence estimation L-estimation M-estimation

Description
Abstract:	We discuss the assumption of symmetry in robust linear regression. It is important to distinguish between the intercept term and the slope parameters. Ordinary robust regression requires no assumption of symmetry when interest lies in slope parameters; computer programs, confidence intervals, standard errors, etc. do not change because the errors are asymmetric. The situation is radically different for bounded influence estimators. With the exception of the Mallows class, these estimators are inconsistent for slope when the errors are asymmetric.
Item Description:	Offprint: American statistician, Volume 42, pages 285-287. Funding information taken from leaf i.
Physical Description:	7 leaves ; 28 cm
Bibliography:	Includes bibliographical references (leaves 6-7).