This chapter examines the role of parameterParametercalibrationCalibrationin the confirmation and validation of complex computer simulation models. I examine the question to what extent calibration data can confirm or validate the calibrated model, focusing in particular on Bayesian approaches to confirmation. I distinguish several different Bayesian approaches to confirmation and argue that complex simulation models exhibit a predictivist effect: Complex computer simulation models constitute a case in which predictive success, as opposed to the mere accommodation of evidence, provides a more stringent test of the model. DataDataused in tuning do not validate or confirm a model to the same extent as data successfully predicted by the model do.
CITATION STYLE
Frisch, M. (2019). Calibration, Validation, and Confirmation (pp. 981–1004). https://doi.org/10.1007/978-3-319-70766-2_41
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