Blind kriging: A new method for developing metamodels

V. Roshan Joseph, Ying Hung, Agus Sudjianto

Research output: Contribution to journalArticlepeer-review

131 Scopus citations


Kriging is a useful method for developing metamodels for product design optimization. The most popular kriging method, known as ordinary kriging, uses a constant mean in the model. In this article, a modified kriging method is proposed, which has an unknown mean model. Therefore, it is called blind kriging. The unknown mean model is identified from experimental data using a Bayesian variable selection technique. Many examples are presented, which show remarkable improvement in prediction using blind kriging over ordinary kriging. Moreover, a blind kriging predictor is easier to interpret and seems to be more robust against mis-specification in the correlation parameters.

Original languageEnglish (US)
Article number031102
JournalJournal of Mechanical Design, Transactions of the ASME
Issue number3
StatePublished - Mar 2008
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design


  • Computer experiments
  • Cross validation
  • Design optimization
  • Finite element models
  • Kriging
  • Metamodels
  • Variable selection


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