Abstract
In the theory of imprecise probability it is often of interest to find the range of the expectation of some function over a convex family of probability measures. Here we show how to find the joint range of the expectations of a finite set of functions when the underlying space is finite and the family of probability distributions is defined by finitely many linear constraints.
| Original language | English (US) |
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| State | Published - 2005 |
| Event | 4th International Symposium on Imprecise Probabilities and Their Applications, ISIPTA 2005 - Pittsburgh, United States Duration: Jul 20 2005 → Jul 23 2005 |
Conference
| Conference | 4th International Symposium on Imprecise Probabilities and Their Applications, ISIPTA 2005 |
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| Country/Territory | United States |
| City | Pittsburgh |
| Period | 7/20/05 → 7/23/05 |
Bibliographical note
Funding Information:Glen Meeden is a Professor in the School of Statistics at the University of Minnesota, 313 Ford Hall, 224 Church St SE, Minneapolis, MN 55455-0493, USA. E-mail: glen@stat.umn.edu. His research was supported in part by NSF grant DMS-0406169.
Publisher Copyright:
© 2005 Society for Imprecise Probability: Theories and Applications, SIPTA. All rights reserved.
Keywords
- Convex family of priors
- Linear constraints
- Polytope
- Probability assessment