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SIAM Journal on Numerical Analysis
Article . 1973 . Peer-reviewed
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Some Methods of Near-Minimax Approximation Using Laguerre Polynomials

Some methods of near-minimax approximation using Laguerre polynomials
Authors: Mason, J. C.;

Some Methods of Near-Minimax Approximation Using Laguerre Polynomials

Abstract

A concept of “near-minimax by characterization” is introduced, which formalizes the idea of an approximation “virtually indistinguishable from minimax.” Certain simple weighted approximation methods and related telescoping procedures, based on orthogonal polynomials, are then discussed in this context. In particular, it is found that, for a suitable $\beta ,e^{ - \lambda x} L_k^{ {- 1}/ 2} (2\lambda \beta x)$ is near-minimax by characterization in approximating the zero function on $[ {0,\infty } )$. It is hence easy to compute rational approximations, near-minimax by characterization, of a most appropriate form to $e^{ - x} $ on $[ {0,\infty } )$.

Keywords

Best approximation, Chebyshev systems, Numerical smoothing, curve fitting

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Top 10%
Average
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