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Title: Model Calibration with Censored Data

Journal Article · · Technometrics
 [1];  [2];  [2];  [1]
  1. Georgia Inst. of Technology, Atlanta, GA (United States)
  2. Procter & Gamble Co., Mason, OH (United States)
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Here, the purpose of model calibration is to make the model predictions closer to reality. The classical Kennedy-O'Hagan approach is widely used for model calibration, which can account for the inadequacy of the computer model while simultaneously estimating the unknown calibration parameters. In many applications, the phenomenon of censoring occurs when the exact outcome of the physical experiment is not observed, but is only known to fall within a certain region. In such cases, the Kennedy-O'Hagan approach cannot be used directly, and we propose a method to incorporate the censoring information when performing model calibration. The method is applied to study the compression phenomenon of liquid inside a bottle. The results show significant improvement over the traditional calibration methods, especially when the number of censored observations is large.

Research Organization:
Georgia Institute of Technology, Atlanta, GA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
Grant/Contract Number:
SC0010548
OSTI ID:
1405186
Report Number(s):
DOE-GT-0010548-11; FG02-13ER26159
Journal Information:
Technometrics, Vol. 60, Issue 2; ISSN 0040-1706
Publisher:
Taylor & FrancisCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 5 works
Citation information provided by
Web of Science

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Linked Research (4)

Figures / Tables (6)

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97 MATHEMATICS AND COMPUTING
Bayesian calibration
Computer experiments
Gaussian process
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