Nonlinear regression modeling via regularized wavelets and smoothing parameter selection

DOI10.1016/j.jmva.2005.12.009zbMath1101.62028OpenAlexW2033900887MaRDI QIDQ855915

Toru Fujii, Sadanori Konishi

Publication date: 7 December 2006

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2005.12.009

zbMATH Keywords

waveletslinear shrinkageautomatic smoothing parameter selectionirregular design pointsregression modeling

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) General nonlinear regression (62J02) Monte Carlo methods (65C05)

Related Items (7)

Wavelet-based estimation of regression function for dependent biased data under a given random design ⋮ Nonparametric Wavelet Regression Based on Biased Data ⋮ Non parametric regression estimations over L^p risk based on biased data ⋮ Multiclass functional discriminant analysis and its application to gesture recognition ⋮ Nonlinear logistic discrimination via regularized radial basis functions for classifying high-dimensional data ⋮ Model selection criteria for the varying-coefficient modelling via regularized basis expansions ⋮ On MISE of a Non linear Wavelet Estimator of the Regression Function Based on Biased Data under Strong Mixing

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