@article { ISI:000302033200021,
	title = {Bandwidth choice for robust nonparametric scale function estimation},
	journal = {COMPUTATIONAL STATISTICS \& DATA ANALYSIS},
	volume = {56},
	number = {6},
	year = {2012},
	month = {JUN},
	pages = {1594-1608},
	publisher = {ELSEVIER SCIENCE BV},
	type = {Article},
	address = {PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS},
	abstract = {We introduce and compare several robust procedures for bandwidth selection when estimating the variance function. These bandwidth selectors are to be used in combination with the robust scale estimates introduced by Boente et al. (2010a). We consider two different robust cross-validation strategies combined with two ways for measuring the cross-validation prediction error. The different proposals are compared with non robust alternatives using Monte Carlo simulation. We also derive some asymptotic results to investigate the large sample performance of the corresponding robust data-driven scale estimators. (C) 2011 Elsevier B.V. All rights reserved.},
	keywords = {Cross-validation, Data-driven bandwidth, Heteroscedasticity, Local M-estimators, nonparametric regression, Robust estimation},
	issn = {0167-9473},
	doi = {10.1016/j.csda.2011.10.002},
	author = {Boente, Graciela and Ruiz, Marcelo and Zamar, Ruben H.}
}
