Means and Variances of Stochastic Vector Products with Applications to Random Linear Models

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1977
Accession Number
ADA041149

Entities

People

  • Gerald G. Jerry Brown
  • Herbert C. Rutemiller

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • California
  • Computational Science
  • Computations
  • Computer Programming
  • Computer Science
  • Inequalities
  • Linear Programming
  • Mathematical Models
  • Mathematics
  • Models
  • Operations Research
  • Probability
  • Probability Distributions
  • Random Variables
  • Schools
  • Simulations

Fields of Study

  • Mathematics

Readers

  • Educational Psychology
  • Linear Algebra
  • Regression Analysis.