Kernel interpolation
Surrogate interpolation models for time-consuming computer experiments are being increasingly used in scientific and engineering problems. A new interpolation method, based on Delaunay triangulations and related to inverse distance weighting, is introduced. This method not only provides an interpolator but also uncertainty bands to judge the local fit, in contrast to methods such as radial basis functions. Compared to the classical Kriging approach, it shows a better performance in specific cases of small data sets and data with non-stationary behavior.
Year of publication: |
2011
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Authors: | Mühlenstädt, Thomas ; Kuhnt, Sonja |
Published in: |
Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 55.2011, 11, p. 2962-2974
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Publisher: |
Elsevier |
Keywords: | Delaunay triangulation Computer experiment Kriging Inverse distance weighting |
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