Model Calibration with Censored Data

• Activity Number: 571 - Statistics for Computer Experiments: Collaboration Between Industry and Academia
• Type: Topic Contributed
• Date/Time: Wednesday, August 2, 2017 : 2:00 PM to 3:50 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Shan Ba* and Fang Cao and William Brenneman and Roshan Joseph Vengazhiyil
• Companies: Procter & Gamble Company and Georgia Institute of Technology and The Procter & Gamble Company and Georgia Institute of Technology
• Keywords: Computer models ; Gaussian process ; Model inadequacy

Abstract

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 and the results show significant improvements over the traditional calibration methods.