Generalized profiling estimation for global and adaptive penalized spline smoothing

We propose the generalized profiling method to estimate the multiple regression functions in the framework of penalized spline smoothing, where the regression functions and the smoothing parameter are estimated in two nested levels of optimization. The corresponding gradients and Hessian matrices ar...

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Veröffentlicht in:	Computational statistics & data analysis Jg. 53; H. 7; S. 2550 - 2562
Hauptverfasser:	Cao, Jiguo, Ramsay, James O.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 15.05.2009 Elsevier
Schriftenreihe:	Computational Statistics & Data Analysis
Schlagworte:	Exact sciences and technology General topics Mathematics Multivariate analysis Numerical analysis Numerical analysis. Scientific computation Numerical methods in probability and statistics Parametric inference Probability and statistics Sciences and techniques of general use Statistics Variance estimation Optimization method Estimator robustness Adaptive estimation Penalty method Optimization Spline Variance Spline approximation Numerical approximation Smoothing parameter Regression function Regression spline Mathematical programming Data analysis Smoothing methods Covariance analysis Variance analysis Multiple regression Delta method Statistical regression Numerical analysis Statistical computation Simulation Smoothing Curvature
ISSN:	0167-9473, 1872-7352
Online-Zugang:	Volltext
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