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:
-
- Georgia Inst. of Technology, Atlanta, GA (United States)
- Procter & Gamble Co., Mason, OH (United States)
- Publication Date:
- Research Org.:
- Georgia Institute of Technology, Atlanta, GA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- OSTI Identifier:
- 1405186
- Report Number(s):
- DOE-GT-0010548-11
Journal ID: ISSN 0040-1706; FG02-13ER26159
- Grant/Contract Number:
- SC0010548
- Resource Type:
- 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. https://doi.org/10.1080/00401706.2017.1345704
Cao, Fang, Ba, Shan, Brenneman, William A., and Joseph, V. Roshan. Wed .
"Model Calibration with Censored Data". United States. https://doi.org/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}
}
Web of Science
Figures / Tables:
Works referenced in this record:
Gravitational Collapse of Colloidal Gels
journal, June 2005
- Manley, S.; Skotheim, J. M.; Mahadevan, L.
- Physical Review Letters, Vol. 94, Issue 21
Computer Model Calibration Using High-Dimensional Output
journal, June 2008
- Higdon, Dave; Gattiker, James; Williams, Brian
- Journal of the American Statistical Association, Vol. 103, Issue 482
Bayesian Calibration of Inexact Computer Models
journal, July 2016
- Plumlee, Matthew
- Journal of the American Statistical Association, Vol. 112, Issue 519
Engineering-Driven Statistical Adjustment and Calibration
journal, April 2015
- Joseph, V. Roshan; Yan, Huan
- Technometrics, Vol. 57, Issue 2
Numerical Computation of Multivariate Normal Probabilities
journal, June 1992
- Genz, Alan
- Journal of Computational and Graphical Statistics, Vol. 1, Issue 2
Surrogate Preposterior Analyses for Predicting and Enhancing Identifiability in Model Calibration
journal, January 2015
- Jiang, Zhen; Apley, Daniel W.; Chen, Wei
- International Journal for Uncertainty Quantification, Vol. 5, Issue 4
Some results on the multivariate truncated normal distribution
journal, May 2005
- Horrace, William C.
- Journal of Multivariate Analysis, Vol. 94, Issue 1
Bayesian Computation Using Design of Experiments-Based Interpolation Technique
journal, August 2012
- Joseph, V. Roshan
- Technometrics, Vol. 54, Issue 3
Bayesian calibration of computer models
journal, August 2001
- Kennedy, Marc C.; O'Hagan, Anthony
- Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 63, Issue 3
On Moments of Folded and Truncated Multivariate Normal Distributions
journal, October 2017
- Kan, Raymond; Robotti, Cesare
- Journal of Computational and Graphical Statistics, Vol. 26, Issue 4
Bayesian Additive Regression Tree Calibration of Complex High-Dimensional Computer Models
journal, April 2016
- Pratola, M. T.; Higdon, D. M.
- Technometrics, Vol. 58, Issue 2
Numerical Computation of Multivariate Normal Probabilities
journal, June 1992
- Genz, Alan
- Journal of Computational and Graphical Statistics, Vol. 1, Issue 2
The Normal Law Under Linear Restrictions: Simulation and Estimation via Minimax Tilting
text, January 2016
- Botev, Z. I.
- arXiv
Model Calibration Through Minimal Adjustments
journal, October 2014
- Chang, Chia-Jung; Joseph, V. Roshan
- Technometrics, Vol. 56, Issue 4
A Framework for Validation of Computer Models
journal, May 2007
- Bayarri, Maria J.; Berger, James O.; Paulo, Rui
- Technometrics, Vol. 49, Issue 2
The normal law under linear restrictions: simulation and estimation via minimax tilting
journal, February 2016
- Botev, Z. I.
- Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 79, Issue 1
Tobit models: A survey
journal, January 1984
- Amemiya, Takeshi
- Journal of Econometrics, Vol. 24, Issue 1-2
Efficient Calibration for Imperfect Computer Models
preprint, January 2015
- Tuo, Rui; Wu, C. F. Jeff
- arXiv
Gaussian predictive process models for large spatial data sets
journal, September 2008
- Banerjee, Sudipto; Gelfand, Alan E.; Finley, Andrew O.
- Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 70, Issue 4
Efficient calibration for imperfect computer models
journal, December 2015
- Tuo, Rui; Wu, C. F. Jeff
- The Annals of Statistics, Vol. 43, Issue 6
Prediction and Computer Model Calibration Using Outputs From Multifidelity Simulators
journal, November 2013
- Goh, Joslin; Bingham, Derek; Holloway, James Paul
- Technometrics, Vol. 55, Issue 4
Bayesian Validation of Computer Models
journal, November 2009
- Wang, Shuchun; Chen, Wei; Tsui, Kwok-Leung
- Technometrics, Vol. 51, Issue 4
Figures / Tables found in this record: