A Framework for Validation of Computer Models

• Published in: Technometrics Vol. 49; no. 2; pp. 138 - 154
• Main Authors: Bayarri, Maria J, Berger, James O, Paulo, Rui, Sacks, Jerry, Cafeo, John A, Cavendish, James, Lin, Chin-Hsu, Tu, Jian
• Format: Journal Article
• Language: English
• Published: Alexandria, VI Taylor & Francis 01.05.2007; Milwaukee, WI The American Society for Quality and The American Statistical Association; American Society for Quality Control; American Statistical Association; American Society for Quality
• Subjects: Accuracy; Applied sciences; Approximation; Bayesian analysis; Bias; Calibration; Computer analysis; Computer based modeling; Computer modeling; Computer science; control theory; systems; Data models; Data processing. List processing. Character string processing; Exact sciences and technology; Identifiability; Mathematics; Maximum likelihood estimation; Memory organisation. Data processing; Model discrepancy; Modeling; Motivation; Parametric models; Prediction; Probability and statistics; Sciences and techniques of general use; Software; Statistics; Studies; Validity; Welding; Bayes estimation; Multimodel; Information validation; Identifiability; Model discrepancy; Information source; Multiplicity; Prediction; Spot welding; Updating; Modeling; Bayesian analysis

We present a framework that enables computer model evaluation oriented toward answering the question: Does the computer model adequately represent reality? The proposed validation framework is a six-step procedure based on Bayesian and likelihood methodology. The Bayesian methodology is particularly...