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Mathematics of Computation

Published by the American Mathematical Society since 1960 (published as Mathematical Tables and other Aids to Computation 1943-1959), Mathematics of Computation is devoted to research articles of the highest quality in computational mathematics.

ISSN 1088-6842 (online) ISSN 0025-5718 (print)

The 2020 MCQ for Mathematics of Computation is 1.78.

What is MCQ? The Mathematical Citation Quotient (MCQ) measures journal impact by looking at citations over a five-year period. Subscribers to MathSciNet may click through for more detailed information.


The approximation power of moving least-squares
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by David Levin PDF
Math. Comp. 67 (1998), 1517-1531 Request permission


A general method for near-best approximations to functionals on $\mathbb {R}^d$, using scattered-data information is discussed. The method is actually the moving least-squares method, presented by the Backus-Gilbert approach. It is shown that the method works very well for interpolation, smoothing and derivatives’ approximations. For the interpolation problem this approach gives Mclain’s method. The method is near-best in the sense that the local error is bounded in terms of the error of a local best polynomial approximation. The interpolation approximation in $\mathbb {R}^d$ is shown to be a $C^\infty$ function, and an approximation order result is proven for quasi-uniform sets of data points.
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Additional Information
  • David Levin
  • Affiliation: School of Mathematical Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel
  • Email:
  • Received by editor(s): September 7, 1995
  • Received by editor(s) in revised form: September 4, 1996, and March 28, 1997
  • © Copyright 1998 American Mathematical Society
  • Journal: Math. Comp. 67 (1998), 1517-1531
  • MSC (1991): Primary 41A45; Secondary 41A25
  • DOI:
  • MathSciNet review: 1474653