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An integral estimator of residual variance and a measure of explanatory power of covariates in nonparametric regression

Authors: Pascal Lavergne ^a; Quang H. Vuong ^b

Affiliations:	^a INRA-ESR Toulouse,
	^b University of Southern California, INRA-ESR Toulouse

DOI: 10.1080/10485259808832750

Publication Frequency: 8 issues per year

Published in: journal

Journal of Nonparametric Statistics, Volume 9, Issue 4 1998 , pages 363 - 380

Subjects: Mathematical Economics; Mathematical Finance; Medical Statistics; Statistical Theory & Methods; Statistics; Statistics for the Biological Sciences; Stochastic Models & Processes;

Formats available: PDF (English)

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Abstract

We propose a new estimator of unconditional residual variance in nonparametric regression based on the integral of squared residuals. We show its consistency in l rcub

under general conditions and derive a nonparametric decomposition of the variance formula. Monte-Carlo experiments suggest that the estimator has good small sample properties.

Keywords: Residual variance; nonparametric R-squared

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An integral estimator of residual variance and a measure of explanatory power of covariates in nonparametric regression

Abstract