Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/36581
Authors: 
Bissantz, Nicolai
Dümbgen, Lutz
Holzmann, Hajo
Munk, Axel
Year of Publication: 
2007
Series/Report no.: 
Technical Report // Sonderforschungsbereich 475, Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund 2007,03
Abstract: 
Uniform confidence bands for densities f via nonparametric kernel estimates were first constructed by Bickel and Rosenblatt [Ann. Statist. 1, 1071.1095]. In this paper this is extended to confidence bands in the deconvolution problem g = f for an ordinary smooth error density . Under certain regularity conditions, we obtain asymptotic uniform confidence bands based on the asymptotic distribution of the maximal deviation (LÉ-distance) between a deconvolution kernel estimator . f and f. Further consistency of the simple nonparametric bootstrap is proved. For our theoretical developments the bias is simply corrected by choosing an undersmoothing bandwidth. For practical purposes we propose a new data-driven bandwidth selector based on heuristic arguments, which aims
Document Type: 
Working Paper

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