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Title: Model Calibration with Censored Data

Abstract

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.

Authors:
 [1];  [2];  [2];  [1]
  1. Georgia Inst. of Technology, Atlanta, GA (United States)
  2. Procter & Gamble Co., Mason, OH (United States)
Publication Date:
Research Org.:
Georgia Tech Research Corp., Atlanta, GA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1405186
Report Number(s):
DOE-GT-0010548-11
Journal ID: ISSN 0040-1706; FG02-13ER26159
Grant/Contract Number:  
SC0010548
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Technometrics
Additional Journal Information:
Journal Volume: 60; Journal Issue: 2; Journal ID: ISSN 0040-1706
Publisher:
Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Bayesian calibration; Computer experiments; Gaussian process; Model discrepancy

Citation Formats

Cao, Fang, Ba, Shan, Brenneman, William A., and Joseph, V. Roshan. Model Calibration with Censored Data. United States: N. p., 2017. Web. doi:10.1080/00401706.2017.1345704.
Cao, Fang, Ba, Shan, Brenneman, William A., & Joseph, V. Roshan. Model Calibration with Censored Data. United States. doi:10.1080/00401706.2017.1345704.
Cao, Fang, Ba, Shan, Brenneman, William A., and Joseph, V. Roshan. Wed . "Model Calibration with Censored Data". United States. doi:10.1080/00401706.2017.1345704. https://www.osti.gov/servlets/purl/1405186.
@article{osti_1405186,
title = {Model Calibration with Censored Data},
author = {Cao, Fang and Ba, Shan and Brenneman, William A. and Joseph, V. Roshan},
abstractNote = {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.},
doi = {10.1080/00401706.2017.1345704},
journal = {Technometrics},
number = 2,
volume = 60,
place = {United States},
year = {Wed Jun 28 00:00:00 EDT 2017},
month = {Wed Jun 28 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
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