A Framework for Validation of Computer Models
Universitat de València · Duke University · +5 more institutions
Abstract
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 well suited to treating the major issues associated with the validation process: quantifying multiple sources of error and uncertainty in computer models, combining multiple sources of information, and updating validation assessments as new information is acquired. Moreover, it allows inferential statements to be made about predictive error associated with model predictions in untested situations. The framework is…
Citation impact
- FWCI
- 27.67
- Percentile
- 100%
- References
- 48
Authors
8Topics & keywords
- Computer science
- Data mining
- Process (computing)
- Context (archaeology)
- Bayesian probability
- Machine learning
- Artificial intelligence
- Programming language