A Data Based Random Number Generator for a Multivariate Distribution - A Users' Manual

Abstract

Let X be a k-dimensional random variable serving as input for a system with output Y(not necessarily of dimension k). Given X, an outcome Y or a distribution of outcomes G(Y/X) may be obtained either explicitly or implicitly. We consider here the situation in which we have a real world data set X (J) to the nth power (j=1) to the n power and a means of simulating an outcome Y. A method for empirical random number generation based on the sample of observations of the random variable X without estimating the underlying density is discussed.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1982
Accession Number
ADA121571

Entities

People

  • Barry A. Bodt
  • Malcolm S. Taylor

Organizations

  • Ballistic Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programs
  • Computers
  • Covariance
  • Data Science
  • Data Sets
  • Databases
  • Four Dimensional
  • Information Science
  • Knowledge Management
  • Monte Carlo Method
  • Random Number Generators
  • Random Variables
  • Simulations
  • Statistical Distributions
  • Statistical Samples
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Statistical inference.