Penalized likelihood kriging model for analysis of computer experiments

Runze Li, Agus Sudjianto

Research output: Contribution to conferencePaper

8 Scopus citations

Abstract

Kriging is a popular metamodeling technique for analysis of computer experiment. However, the likelihood function near the optimum is flat in some situations, and this may lead to very large random variation in the maximum likelihood estimate. To overcome this difficulty, a penalized likelihood approach is proposed for the kriging model. The proposed method is particularly important in the context of a computationally intensive simulation model where the number of simulation runs must be kept small. We demonstrate the proposed approach for the reduction of piston slap, an unwanted engine noise due to piston secondary motion. Issues related to practical implementation of the proposed approach are discussed.

Original languageEnglish (US)
Pages527-533
Number of pages7
DOIs
StatePublished - 2003
Event2003 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Chicago, IL, United States
Duration: Sep 2 2003Sep 6 2003

Other

Other2003 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference
CountryUnited States
CityChicago, IL
Period9/2/039/6/03

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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    Li, R., & Sudjianto, A. (2003). Penalized likelihood kriging model for analysis of computer experiments. 527-533. Paper presented at 2003 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Chicago, IL, United States. https://doi.org/10.1115/detc2003/dac-48758