@article { ISI:000319173400020,
	title = {Robust and efficient estimation of the residual scale in linear regression},
	journal = {JOURNAL OF MULTIVARIATE ANALYSIS},
	volume = {116},
	year = {2013},
	month = {APR},
	pages = {278-296},
	publisher = {ELSEVIER INC},
	type = {Article},
	address = {525 B STREET, STE 1900, SAN DIEGO, CA 92101-4495 USA},
	abstract = {Robustness and efficiency of the residual scale estimators in the regression model is important for robust inference. We introduce the class of robust generalized M-scale estimators for the regression model, derive their influence function and gross-error sensitivity, and study their maxbias behavior. In particular, we find overall minimax bias estimates for the general class and also for well-known subclasses. We pose and solve a Hampers-like optimality problem: we find generalized M-scale estimators with maximal efficiency subject to a lower bound on the global and local robustness of the estimators. (C) 2013 Elsevier Inc. All rights reserved.},
	keywords = {Efficiency, Gross-error sensitivity, influence function, Maxbias, Robust scale},
	issn = {0047-259X},
	doi = {10.1016/j.jmva.2012.12.008},
	author = {Van Aelst, Stefan and Willems, Gert and Zamar, Ruben H.}
}
