Calibration for Computer Experiments With Binary Responses and Application to Cell Adhesion Study

• 成果类型: Article
• 署名作者: Sung, Chih-Li; Hung, Ying; Rittase, William; Zhu, Cheng; Wu, C. F. J.
• 署名单位: Michigan State University; Rutgers University System; Rutgers University New Brunswick; University System of Georgia; Georgia Institute of Technology; University System of Georgia; Georgia Institute of Technology
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2019.1699419
• 发表日期: 2020
• 页码: 1664-1674
• 关键词: bayesian calibration; MODEL; kinetics; memory

摘要

Calibration refers to the estimation of unknown parameters which are present in computer experiments but not available in physical experiments. An accurate estimation of these parameters is important because it provides a scientific understanding of the underlying system which is not available in physical experiments. Most of the work in the literature is limited to the analysis of continuous responses. Motivated by a study of cell adhesion experiments, we propose a new calibration framework for binary responses. Its application to the T cell adhesion data provides insight into the unknown values of the kinetic parameters which are difficult to determine by physical experiments due to the limitation of the existing experimental techniques. for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.