Mean and variance bounds and propagation for ill-specified random variables

Authors:
A. T. Langewisch;F. F. Choobineh
Affiliations:
Dept. of Bus. Adm., Concordia Univ., Seward, USA;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Year:
2004

Citing 0
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Interval-based robust statistical techniques for non-negative convex functions, with application to timing analysis of computer chips

Proceedings of the 2006 ACM symposium on Applied computing

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Abstract

Foundations, models, and algorithms are provided for identifying optimal mean and variance bounds of an ill-specified random variable. A random variable is ill-specified when at least one of its possible realizations and/or its respective probability mass is not restricted to a point but rather belongs to a set or an interval. We show that a nonexhaustive sensitivity-analysis approach does not always identify the optimal bounds. Also, a procedure for determining the mean and variance bounds of an arithmetic function of ill-specified random variables is presented. Estimates of pairwise correlation among the random variables can be incorporated into the function. The procedure is illustrated in the context of a case study in which exposure to contaminants through the inhalation pathway is modeled.