Uncertainty is a key issue in decision analysis and other kinds of applications. Researchers have developed a numbers of approaches to address computations on uncertain quantities. When doing arithmetic operations on random variables, an important question has to be considered: the dependency relationships among the variables. In practice, we often have partial information about the dependency relationship between two random variables. This information may result from experience or system requirements. We can use this information to improve bounds on the cumulative distributions of random variables derived from the marginals whose dependency is partially known.
Keywords. Uncertainty, arithmetic on random variables, distribution envelope determination (DEnv), joint distribution, dependency relationship, copulas, probability boxes, linear programming, partial information.
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Authors addresses:
Jianzhong Zhang
145F university village
Ames, IA 50010
Dan Berleant
Dept. of Electrical and Computer Engineering
Iowa State University
3215 Coover Hall
50011 Ames, Iowa
USA
E-mail addresses:
| Jianzhong Zhang | zjz@iastate.edu |
| Dan Berleant | berleant@iastate.edu |