Analysis of computer experiments with functional response

Ying Hung, V. Roshan Joseph, Shreyes N. Melkote

Research output: Contribution to journalArticlepeer-review

38 Scopus citations


This article is motivated by a computer experiment conducted for optimizing residual stresses in the machining of metals. Although kriging is widely used in the analysis of computer experiments, it cannot be easily applied to model the residual stresses because they are obtained as a profile. The high dimensionality caused by this functional response introduces severe computational challenges in kriging. It is well known that if the functional data are observed on a regular grid, the computations can be simplified using an application of Kronecker products. However, the case of irregular grid is quite complex. In this article, we develop a Gibbs sampling-based expectation maximization algorithm, which converts the irregularly spaced data into a regular grid so that the Kronecker product-based approach can be employed for efficiently fitting a kriging model to the functional data. Supplementary materials are available online.

Original languageEnglish (US)
Pages (from-to)35-44
Number of pages10
Issue number1
StatePublished - Jan 2 2015

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Applied Mathematics


  • EM algorithm
  • Gaussian process model
  • Gibbs sampling
  • Kriging
  • Latin hypercube design
  • Optimization


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