Bandwidth choice for robust nonparametric scale function estimation

• Published in: Computational statistics & data analysis Vol. 56; no. 6; pp. 1594 - 1608
• Main Authors: Boente, Graciela, Ruiz, Marcelo, Zamar, Ruben H.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-06-2012; Elsevier
• Series: Computational Statistics & Data Analysis
• Subjects: Asymptotic properties; Bandwidth; Computer simulation; Cross-validation; Cross-validation Data-driven bandwidth Heteroscedasticity Local M-estimators Nonparametric regression Robust estimation; Data-driven bandwidth; Estimating; Heteroscedasticity; Local [formula omitted]-estimators; Mathematical analysis; Mathematical models; Monte Carlo methods; Nonparametric regression; Robust estimation; Statistical methods; Local M-estimators; Robust estimation; Data-driven bandwidth; Cross-validation; Nonparametric regression; Heteroscedasticity
• ISSN: 0167-9473; 1872-7352
• DOI: 10.1016/j.csda.2011.10.002

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.