ANOVA approximation with mixed tensor product basis on scattered points

Fuente: arXiv
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Autori principali: Potts, Daniel, Schröter, Pascal
Natura: Preprint
Pubblicazione: 2023
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author Potts, Daniel
Schröter, Pascal
author_facet Potts, Daniel
Schröter, Pascal
contents In this paper we consider an orthonormal basis, generated by a tensor product of Fourier basis functions, half period cosine basis functions, and the Chebyshev basis functions. We deal with the approximation problem in high dimensions related to this basis and design a fast algorithm to multiply with the underlying matrix, consisting of rows of the non-equidistant Fourier matrix, the non-equidistant cosine matrix and the non-equidistant Chebyshev matrix, and its transposed. This leads us to an ANOVA (analysis of variance) decomposition for functions with partially periodic boundary conditions through using the Fourier basis in some dimensions and the half period cosine basis or the Chebyshev basis in others. We consider sensitivity analysis in this setting, in order to find an adapted basis for the underlying approximation problem. More precisely, we find the underlying index set of the multidimensional series expansion. Additionally, we test this ANOVA approximation with mixed basis at numerical experiments, and refer to the advantage of interpretable results.
format Preprint
id arxiv_https___arxiv_org_abs_2306_09174
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle ANOVA approximation with mixed tensor product basis on scattered points
Potts, Daniel
Schröter, Pascal
Numerical Analysis
65T, 42B05
In this paper we consider an orthonormal basis, generated by a tensor product of Fourier basis functions, half period cosine basis functions, and the Chebyshev basis functions. We deal with the approximation problem in high dimensions related to this basis and design a fast algorithm to multiply with the underlying matrix, consisting of rows of the non-equidistant Fourier matrix, the non-equidistant cosine matrix and the non-equidistant Chebyshev matrix, and its transposed. This leads us to an ANOVA (analysis of variance) decomposition for functions with partially periodic boundary conditions through using the Fourier basis in some dimensions and the half period cosine basis or the Chebyshev basis in others. We consider sensitivity analysis in this setting, in order to find an adapted basis for the underlying approximation problem. More precisely, we find the underlying index set of the multidimensional series expansion. Additionally, we test this ANOVA approximation with mixed basis at numerical experiments, and refer to the advantage of interpretable results.
title ANOVA approximation with mixed tensor product basis on scattered points
topic Numerical Analysis
65T, 42B05
url https://arxiv.org/abs/2306.09174