f_2D

<p>The evaluations were obtained by using the \(\texttt{fda}\) package with 10000 input values contained in the xpred_2D.rda file.</p>

Generalized LassO applied to knot selection in multivariate B-splinE Regression (GLOBER) implements a novel approach for estimating functions in a multivariate nonparametric regression model based on an adaptive knot selection for B-splines using the Generalized Lasso. For further details we refer the reader to the paper Savino, M. E. and Lévy-Leduc, C. (2023), <arXiv:2306.00686>.

Mary Savino

glober

Estimating Functions with Multivariate B-Splines

f_2D function

Format

Output values of the evaluation of a function with two input variables and defined as a linear combination of a tensor product of univariate B-splines — f_2D

f_2D: Output values of the evaluation of a function with two input variables and defined as a linear combination of a tensor product of univariate B-splines

Description

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