Quadratic deviation of penalized mean squares regression estimates

Our aim in this work is to give a global test of hypothesis concerning the smoothing spline estimate of a regression function. For this, we prove a central limit theorem for integrated squares of such estimates. That leads to a test whose confidence sets are either continuous or discrete L2-balls. We consider the case of nonperiodic splines and the periodic splines for which we get explicit expressions of the constants involved in such a test.

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Year of publication:	1992
Authors:	Doukhan, Paul ; Gassiat, Elisabeth
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 41.1992, 1, p. 89-101
Publisher:	Elsevier
Subject:	limit theorem nonparametric interference: hypothesis testing \| penalized mean squares estimates regression and correlation: general nonlinear regression \| smoothing splines regression estimates

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005199486