Comparison of Gaussian process modeling software

Collin B. Erickson*, Bruce E. Ankenman, Susan M. Sanchez

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Gaussian process fitting, or kriging, is often used to create a model from a set of data. Many available software packages do this, but we show that very different results can be obtained from different packages even when using the same data and model. We describe the parameterization, features, and optimization used by eight different fitting packages that run on four different platforms. We then compare these eight packages using various data functions and data sets, revealing that there are stark differences between the packages. In addition to comparing the prediction accuracy, the predictive variance – which is important for evaluating precision of predictions and is often used in stopping criteria – is also evaluated.

Original languageEnglish (US)
Pages (from-to)179-192
Number of pages14
JournalEuropean Journal of Operational Research
Volume266
Issue number1
DOIs
StatePublished - Apr 1 2018

Keywords

  • Computer experiments
  • Gaussian processes
  • Metamodels
  • Simulation
  • Stochastic kriging

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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