IMPRECISE PROBABILITIES AND THEIR APPLICATIONS

30 June - 2 July 1999

** Abstract **

The concept of interval-probability is motivated by the goal to generalize classical probability so that it can be used for describing uncertainty in general. The foundations of the theory are based on a system of three axioms -- in addition to Kolmogorov's axioms -- and definitions of independence as well as of conditional probability. The resulting theory does not depend upon interpretations of the probability concept. As an example of generalizing classical results the Bayes' rule is described -- other theorems are only mentioned.

** Keywords. ** Interval-probability, uncertainty, conditional probability, Bayes' Rule

The paper is available in the following formats and sites:

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- Postscript file (Granada - Spain)
- Postscript file (Sao Paulo - Brasil)
- Postscript file (Gent - Belgium)
- Gzipped pdf file (Granada - Spain)
- pdf file (Granada - Spain)
- pdf file (Sau Paulo - Brasil)
- pdf file (Gent - Belgium)

Prof. Kurt Weichselberger

Department of Statistics

Ludwigstr. 33/I

D 80539 Munich

** E-mail addresses: **

Kurt Weichselberger | weichsel@stat.uni-muenchen.de |

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