On the unbiasedness of robust regression estimators
- 1 January 1978
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 7 (8) , 779-783
- https://doi.org/10.1080/03610927808827668
Abstract
A simple proof of the unbiasedness of L -norm and M-estimators is given for regression models.Keywords
This publication has 7 references indexed in Scilit:
- Norm Minimizing Estimation and UnbiasednessEconometrica, 1976
- A Robust Method for Multiple Linear RegressionTechnometrics, 1974
- An Iterative Technique for Absolute Deviations Curve FittingJournal of the American Statistical Association, 1973
- Two Linear Programming Algorithms for Unbiased Estimation of Linear ModelsJournal of the American Statistical Association, 1973
- Robust Regression: Asymptotics, Conjectures and Monte CarloThe Annals of Statistics, 1973
- Robust Estimation of Straight Line Regression Coefficients by Minimizing pth Power DeviationsTechnometrics, 1972
- The Unbiasedness of Zellner's Seemingly Unrelated Regression Equations EstimatorsJournal of the American Statistical Association, 1967