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Smooth supersaturated models

Bates, Ron A., Maruri-Aguilar, Hugo and Wynn, Henry P. ORCID: 0000-0002-6448-1080 (2014) Smooth supersaturated models. Journal of Statistical Computation and Simulation, 84 (11). pp. 2453-2464. ISSN 0094-9655

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Identification Number: 10.1080/00949655.2013.823428


In areas such as kernel smoothing and non-parametric regression, there is emphasis on smooth interpolation. We concentrate on pure interpolation and build smooth polynomial interpolators by first extending the monomial (polynomial) basis and then minimizing a measure of roughness with respect to the extra parameters in the extended basis. Algebraic methods can help in choosing the extended basis. We get arbitrarily close to optimal smoothing for any dimension over an arbitrary region, giving simple models close to splines. We show in examples that smooth interpolators perform much better than straight polynomial fits and for small sample size, better than kriging-type methods, used, for example in computer experiments.

Item Type: Article
Official URL:
Additional Information: © 2014 Taylor and Francis Ltd.
Divisions: LSE
Subjects: H Social Sciences > HA Statistics
H Social Sciences > HC Economic History and Conditions
Date Deposited: 08 Aug 2014 11:29
Last Modified: 20 Oct 2021 00:49

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