Probability and conditional moments of multivariate uniform random variables satisfying a linear inequality constraint

Marc Mignolet, Chung Chih Lin

Research output: Contribution to journalArticle

2 Scopus citations


A computational technique is presented to evaluate a class of probabilities and expectations of multivariate uniform random variables encountered in the analysis of certain random mechanical systems. First, a finite series representation is derived for the probability that a linear combination of n independent random variables uniformly distributed in the interval [0, 1] does not exceed a given threshold. This exact representation is then used to obtain closed from expressions for various moments, means in particular, of uniform random variables conditional on a linear inequality constraint. Finally, various practical implementation aspects of these computations are discussed and a comparison with the Monte Carlo simulation method is conducted that validates the use of the proposed technique.

Original languageEnglish (US)
Pages (from-to)65-74
Number of pages10
JournalProbabilistic Engineering Mechanics
Issue number2
StatePublished - 1992


ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Civil and Structural Engineering
  • Nuclear Energy and Engineering
  • Condensed Matter Physics
  • Aerospace Engineering
  • Ocean Engineering
  • Mechanical Engineering

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