Smoothing Techniques for Curve Estimation

T. Gasser

ISBN 10: 3540097066 / ISBN 13: 9783540097068

Editore: Springer, Springer Nov 1979, 1979

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This item is printed on demand - Print on Demand Titel. Neuware -Nonparametric curve estimation.- A tree-structured approach to nonparametric multiple regression.- Kernel estimation of regression functions.- Total least squares.- Some theoretical results on Tukey¿s 3R smoother.- Bias- and efficiency-robustness of general M-estimators for regression with random carriers.- Approximate conditional-mean type smoothers and interpolators.- Optimal convergence properties of kernel estimates of derivatives of a density function.- Density quantile estimation approach to statistical data modelling.- Global measures of deviation for kernel and nearest neighbor density estimates.- Some comments on the asymptotic behavior of robust smoothers.- Cross-validation techniques for smoothing spline functions in one or two dimensions.- Convergence rates of 'thin plate' smoothing splines wihen the data are noisy.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 256 pp. Englisch.

Codice articolo 9783540097068

Dati bibliografici

• Titolo: Smoothing Techniques for Curve Estimation
• Editore: Springer, Springer Nov 1979
• Data di pubblicazione: 1979
• Lingua: Inglese
• ISBN 10: 3540097066
• ISBN 13: 9783540097068
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 15 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 15 millimetri di profondità
• Peso: 394 grammi

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Contenuti

Nonparametric curve estimation.- A tree-structured approach to nonparametric multiple regression.- Kernel estimation of regression functions.- Total least squares.- Some theoretical results on Tukey’s 3R smoother.- Bias- and efficiency-robustness of general M-estimators for regression with random carriers.- Approximate conditional-mean type smoothers and interpolators.- Optimal convergence properties of kernel estimates of derivatives of a density function.- Density quantile estimation approach to statistical data modelling.- Global measures of deviation for kernel and nearest neighbor density estimates.- Some comments on the asymptotic behavior of robust smoothers.- Cross-validation techniques for smoothing spline functions in one or two dimensions.- Convergence rates of "thin plate" smoothing splines wihen the data are noisy.