Means and variances of stochastic vector products with applications to random linear models
By: by Gerald G. Brown and Herbert C. Rutemiller
Contributors: Rutemiller, Herbert Charles; Naval Postgraduate School (U.S.)
Publisher: Naval Postgraduate School
Published: 1977
Place of publication: Monterey, Calif
Language: eng
Number of pages: 18
Subjects: Random variables; Stochastic programming; Operations research
Description: Many mathematical models in operations research require computation of products of vectors whose elements are random variables. Unfortunately, analytic results for functions of interest are only obtained through highly restrictive, often unrealistic, choices of prior densities for the vectors' elements. Often, an investigation is performed by discretizing the random variables at point-quantile levels, or by outright simulation. This paper addresses the problem of characterizing the inner product of two stochastic vectors with arbitrary multivariate densities. Expressions for means of variances of vector products are obtained, and used to make Tchebycheff-type probability statements. Included are applications to stochastic programming models. (Author)
Notes: Title from cover.

"February 1977"--Cover.

"NPS-55-77-6"--Cover.

Author(s) subject terms: Random linear models, stochastic programming, chance constrained linear programming, Tchebycheff inequalities, joint Tchebycheff bounds, dependent stochastic vector products, moments of dependent stochastic vector products.

Includes bibliographical references (p. 14-15)

"Approved for public release; distribution unlimited"--Cover.

Technical report; 1977.