Imprecise probability models and their applications

Imprecise probability models and their applications

This special issue of the International Journal of Approximate Reasoning (IJAR) grew out of the 5th International Symposium on Imprecise Probabilities and Their Applications (ISIPTA’07), held in the beautiful city of Prague, Czech Republic, in July 2007 (http://www.sipta.org/isipta07). The symposium was organized by Gert de Cooman, Jiřina Vejnarová, and Marco Zaffalon. The term imprecise probab...

Validation of imprecise probability models

Validation is the assessment of the match between a model’s predictions and any empirical observations relevant to those predictions. This comparison is straightforward when the data and predictions are deterministic, but is complicated when either or both are expressed in terms of uncertain numbers (i.e., intervals, probability distributions, p-boxes, or more general imprecise probability stru...

Imprecise Probability: Theories and Applications (ISIPTA'13)

Imprecise Probability

Imprecise Probability

1 Overview Quantification of uncertainty is mostly done by the use of precise probabilities: for each event A, a single (classical, precise) probability P (A) is used, typically satisfying Kolmogorov's axioms [4]. Whilst this has been very successful in many applications, it has long been recognized to have severe limitations. Classical probability requires a very high level of precision and co...