Computing mean and variance under Dempster-Shafer uncertainty: Towards faster algorithms

In many real-life situations, we only have partial information about the actual probability distribution. For example, under Dempster-Shafer uncertainty, we only know the masses m1, . . . , mn assigned to different sets S1, . . . , Sn, but we do not know the distribution within each set Si. Because of this uncertainty, there are many possible probability distributions consistent with our knowledge; different distributions have, in general, different values of standard statistical characteristics such as mean and variance. It is therefore desirable, given a Dempster-Shafer knowledge base, to compute the ranges [E, E] and [V , V ] of possible values of mean E and of variance V . In their recent paper, A. T. Langewisch and F. F. Choobineh show how to compute these ranges in polynomial time. In particular, they reduce the problem of computing V to the problem of minimizing a convex quadratic function, a problem which can be solved in time O(n2

• Type: Journal
• Year: 2006
• Where: IJAR
• Authors: Vladik Kreinovich, Gang Xiang, Scott Ferson
• Keywords: Actual Probability Distribution, IJAR 2006, Probability Distribution, Real-life Situations