Comparison of Gaussian process modeling software

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 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. Seven different fitting packages that run on four different platforms are compared using various data functions and data sets that reveal 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)
Title of host publication2016 Winter Simulation Conference
Subtitle of host publicationSimulating Complex Service Systems, WSC 2016
EditorsTheresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3692-3693
Number of pages2
ISBN (Electronic)9781509044863
DOIs
StatePublished - Jul 2 2016
Event2016 Winter Simulation Conference, WSC 2016 - Arlington, United States
Duration: Dec 11 2016Dec 14 2016

Publication series

NameProceedings - Winter Simulation Conference
Volume0
ISSN (Print)0891-7736

Other

Other2016 Winter Simulation Conference, WSC 2016
CountryUnited States
CityArlington
Period12/11/1612/14/16

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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  • Cite this

    Erickson, C., Ankenman, B. E., & Sanchez, S. M. (2016). Comparison of Gaussian process modeling software. In T. M. Roeder, P. I. Frazier, R. Szechtman, & E. Zhou (Eds.), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016 (pp. 3692-3693). [7822403] (Proceedings - Winter Simulation Conference; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2016.7822403