Title: Validation of imprecise probability models

Authors: Scott Ferson, William L. Oberkampf

Addresses: Applied Biomathematics, 100 North Country Road, Setauket, New York 11733, USA. ' 2014 Monte Largo NE, Albuquerque, New Mexico 87112, USA

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; L1 metric; area metric; imprecise probability models; uncertain numbers.

DOI: 10.1504/IJRS.2009.026832

International Journal of Reliability and Safety, 2009 Vol.3 No.1/2/3, pp.3 - 22

Available online: 27 Jun 2009 *

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