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A data based random number generator for a multivariate distribution (using stochastic interpolation)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 implicity. The situation is considered in which there is a real world data set X sub j sub = 1 (n) 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.
Document ID
19830007514
Document Type
Conference Paper
Authors
Thompson, J. R. (Rice Univ. Houston, TX, United States)
Taylor, M. S. (Ballistic Research Lab.)
Date Acquired
August 11, 2013
Publication Date
January 1, 1982
Publication Information
Publication: Texas A and M Univ. Proc. of the NASA Workshop on Density Estimation and Function Smoothing
Subject Category
EARTH RESOURCES AND REMOTE SENSING
Funding Number(s)
CONTRACT_GRANT: DAAG29-82-K-0014
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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IDRelationTitle19830007503Analytic PrimaryProceedings of the NASA Workshop on Density Estimation and Function Smoothing