Quadratic deviation of penalized mean squares regression estimates

Paul Doukhan and Elisabeth Gassiat

Journal of Multivariate Analysis, 1992, vol. 41, issue 1, 89-101

Abstract: 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.

Keywords: limit theorem nonparametric interference: hypothesis testing; penalized mean squares estimates regression and correlation: general nonlinear regression; smoothing splines regression estimates (search for similar items in EconPapers)
Date: 1992
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