Non-parametric estimation of the residual distribution

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2654

Title:	Non-parametric estimation of the residual distribution
Authors:	Akritas, Michael Georgiou VAN KEILEGOM, Ingrid
Issue Date:	2001
Publisher:	BLACKWELL PUBL LTD
Source:	SCANDINAVIAN JOURNAL OF STATISTICS, 28(3). p. 549-567
Abstract:	Consider a heteroscedastic regression model Y = m(X) + sigma (X)epsilon, where the functions m and sigma are "smooth", and epsilon is independent of X. An estimator of the distribution of epsilon based on non-parametric regression residuals is proposed and its weak convergence is obtained. Applications to prediction intervals and goodness-of-fit tests are discussed.
Notes:	Limburgs Univ Ctr, Diepenbeek, Belgium. Penn State Univ, University Pk, PA 16802 USA.Van Keilegom, I, Univ Catholique Louvain, Inst Stat, Voie du Roman Pays 20, B-1348 Louvain, Belgium.
Keywords:	asymptotic representation; goodness-of-fit; non-parametric regression residuals; prediction intervals; residual distribution; weak convergence
Document URI:	http://hdl.handle.net/1942/2654
ISSN:	0303-6898
e-ISSN:	1467-9469
DOI:	10.1111/1467-9469.00254
ISI #:	000170679000010
Category:	A1
Type:	Journal Contribution
Validations:	ecoom 2002
Appears in Collections:	Research publications

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