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Interpolating and Extrapolating

  • Éric WalterEmail author
Chapter

Abstract

Interpolating is not always a good idea and one should be especially careful when extrapolating. These operations are nevertheless sometimes very useful. Classical methods are described for the univariate and multivariate case. Conditions that make very high-degree polynomial interpolation a viable option are explained. Pros and cons of rational interpolation are presented. Richardson’s extrapolation principle is described. It is used, for instance, in numerical integration and differentiation as well as for solving differential equations. Kriging, a multivariate interpolation method initially developed in the context of mining, receives special attention. It is increasingly used in computer experiments to build surrogate models for functions that are very costly to evaluate.

Keywords

Input Factor Polynomial Interpolation Interpolation Point Vandermonde Matrix Rational Interpolation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Laboratoire des Signaux et SystèmesCNRS-SUPÉLEC-Université Paris-SudGif-sur-YvetteFrance

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