Abstract
In this paper we develop an adaptive algorithm for determining the optimal degree of regression in the constrained mock-Chebyshev least-squares interpolation of an analytic function to obtain quadrature formulas with high degree of exactness and accuracy from equispaced nodes. We numerically prove the effectiveness of the proposed algorithm by several examples.
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Di Tommaso F., Francomano E., Dell'Accio F., Nudo F. (2022) "An adaptive algorithm for determining the optimal degree of regression in constrained mock-Chebyshev least squares quadrature
" Dolomites Research Notes on Approximation, 15(4), 35-44. DOI: 10.14658/PUPJ-DRNA-2022-4-4
Year of Publication
2022
Journal
Dolomites Research Notes on Approximation
Volume
15
Issue Number
4
Start Page
35
Last Page
44
Date Published
12/2022
ISSN Number
2035-6803
Serial Article Number
4
DOI
10.14658/PUPJ-DRNA-2022-4-4
Issue
Section
SpecialIssue4