Stable moving least-squares
type: Item
instance of: scholarly article
title: Stable moving least-squares
zbMATH Open document ID: 1182.65022
author: Yaron Lipman
published in: Journal of Approximation Theory
publication date: 2009-11-26T00:00:00Z
review text: Local polynomial fitting in a least squares sense is a common technique in scattered data approximation. However, some known error bounds indicate that the error may become rather large for certain configurations of the given data points. In this paper, the author proves that these bounds are indeed realistic and proposes a modified technique, called stable moving least squares, that leads to better bounds in such worst-case situations.
reviewed by: Kai Diethelm
Mathematics Subject Classification ID: 65D10
Mathematics Subject Classification ID: 41A30
Mathematics Subject Classification ID: 41A63
zbMATH DE Number: 5639050
zbMATH Keywords: moving least squares
zbMATH Keywords: scattered data approximation
zbMATH Keywords: local polynomial fitting
zbMATH Keywords: error bounds
zbMATH Keywords: worst-case situations
MaRDI profile type: Publication
full work available at URL: j.jat.2008.10.011
OpenAlex ID: W2032831583
cites work: Q5564187
cites work: Moving least-squares are Backus-Gilbert optimal
cites work: Q3960030
cites work: Smooth interpolation of large sets of scattered data
cites work: Error estimates for scattered data interpolation on spheres
cites work: Surfaces Generated by Moving Least Squares Methods
cites work: The approximation power of moving least-squares
cites work: Local polynomial reproduction and moving least squares approximation
cites work: Scattered Data Approximation
DOI: 10.1016/J.JAT.2008.10.011
description: scientific article; zbMATH DE number 5639050