Point-wise model validation over experimental regions using regression confidence and tolerance intervals with Bayesian relaxations. (January 2020)

• Record Type: Journal Article
• Authors: Storm, Scott M; Hill, Raymond R; Pignatiello, Joseph J; White, Edward D; Vining, G Geoffrey
• Is Part Of: Simulation. Volume 96:Number 1(2020)
• Page Start: 75
• Page End: 87
• Publication Date: 2020-01
• Subjects: Regression tolerance intervals -- confidence intervals -- model validation -- response surfaces -- experimental design -- Bayesian Hypothesis Testing; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549719844193
• Languages: English
• ISSNs: 0037-5497

Abstract

As systems grow more complex, so does our propensity to use computers to emulate complex real-world systems. Often these real-world systems possess dynamic response behavior over the operational domain of input parameter configurations. This domain is referred to as the design space or experimental region. It is critical we ensure that computer models which emulate such dynamic behavior be validated over the full design space. This paper presents a dual-interval validation methodology. Confidence intervals and tolerance intervals are developed based on a system response surface function. Model samples are compared to each interval to develop a complete model validation conclusion. The methodology is described, its robustness to noise and model lack-of-fit examined, and then it is applied to a well-established engineering validation challenge problem.