Uncertainty in Gaussian Process Interpolation

  • Hilke Kracker
  • Björn Bornkamp
  • Sonja Kuhnt
  • Ursula Gather
  • Katja Ickstadt

Abstract

In this article, we review a probabilistic method for multivariate interpolation based on Gaussian processes. This method is currently a standard approach for approximating complex computer models in statistics, and one of its advantages is the fact that it accompanies the predicted values with uncertainty statements. We focus on investigating the reliability of the method’s uncertainty statements in a simulation study. For this purpose we evaluate the effect of different objective priors and different computational approaches. We illustrate the interpolation method and the practical importance of uncertainty quantification in interpolation in a sequential design application in sheet metal forming. Here design points are added sequentially based on uncertainty statements.

Keywords

Gaussian Process Design Point Uncertainty Statement Sequential Design Posterior Mode 
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-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hilke Kracker
    • 1
  • Björn Bornkamp
    • 1
  • Sonja Kuhnt
    • 1
  • Ursula Gather
    • 1
  • Katja Ickstadt
    • 1
  1. 1.Fakultät StatistikTU DortmundDortmundGermany

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