Validation of imprecise probability models

Scott Ferson and William L. Oberkampf

International Journal of Reliability and Safety, 2009, vol. 3, issue 1/2/3, 3-22

Abstract: Validation is the assessment of the match between a model's predictions and empirical observations. It can be complex when either data or the prediction is characterised as an uncertain number (i.e. interval, probability distribution, p-box, or more general structure). Validation could measure the discrepancy between the shapes of the two uncertain numbers representing prediction and data, or it could characterise the differences between realisations drawn from the respective uncertain numbers. The unification between these two concepts relies on defining the validation measure between prediction and data as the shortest possible distance given the imprecision about the distributions and their dependencies.

Keywords: validation; observation; prediction; distribution; interval; p-box; probability box; L 1 metric; area metric; imprecise probability models; uncertain numbers. (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (13)

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