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Kriging interpolation methods in geostatistics and DACE model

Abstract

In recent study on design of experiments, the complicate metamodeling has been studied because defining exact model using computer simulation is expensive and time consuming. Thus, some designers often use approximate models, which express the relation between some inputs and outputs. In this paper, we review and compare the complicate metamodels, which are expressed by the interaction of various data through trying many physical experiments and running a computer simulation. The prediction model in this paper employs interpolation schemes known as ordinary kriging developed in the fields of spatial statistics and kriging in Design and Analysis of Computer Experiments (DACE) model. We will focus on describing the definitions, the prediction functions and the algorithms of two kriging methods, and assess the error measures of those by using some validation methods.

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Ryu, JS., Kim, MS., Cha, KJ. et al. Kriging interpolation methods in geostatistics and DACE model. KSME International Journal 16, 619–632 (2002). https://doi.org/10.1007/BF03184811

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Key Words

  • Kriging
  • Ordinary Kriging
  • DACE Model
  • Semivariogram
  • Correlation Function
  • BLUP