Iowa State University
Computer Science Department

Presents:
Daniel Berleant,  Associate Professor 
Department of Electrical & Computer Engineering
Iowa State University 

Arithmetic on Random Variables of Unknown Dependency 

Risk and Safety analyses are two examples of tasks that can involve
arithmetic on variables whose values can be uncertain. When two variables
are described by distribution functions, and are known to be independent,
their sum, product, difference, etc. may be found by discretizing the
distributions into intervals and associated probabilities, and reducing the
problem to one of calculations on intervals. The result is bounds on the
distribution function of the result, with finer discretizations yielding
better bounds.
The problem is trickier when the independence assumption is relaxed and no
assumption is permitted about the dependency or lack thereof of the
variables upon each other. An answer is still possible, but is in the form
of a bounded space within which the distribution function of the result must
fall for any given dependency relationship between the two input variables.
Two methods for this are known. I will review the one developed by my
students and I, review how it can be done, and provide copies of a relevant
paper to those interested in the full details of the method. Various curves
and bounds produced by a software package will provide a visual illustration
of the problem.

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Daniel Berleant recently joined the Dept. of Electrical and Computer
Engineering at Iowa State University as an Associate Professor. He received
his PhD from University of Texas at Austin in 1991. In addition to the topic
of this colloquium he also works in the areas of software engineering and
Web Based systems. 

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Thursday, November 18, at 3:40 p.m. in Atanasoff, Room B29
Refreshments will be served afterwards in 225 Atanasoff
http://www.cs.iastate.edu/~colloq/

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Janey Nicholas
Computer Science
226 Atanasoff
294-4377
jnichol@iastate.edu
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