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Constrained Noise for Masking Microdata Records
Constrained Noise for Masking Microdata Records
RR90-04
Abstract
The objective of this report is to present two algorithms which transform data generated by a random number generator into data satisfying certain constraints on means and variance-covariance structure. One algorithm uses a linear transformation and translation to force data generated from a multivariate normal distribution to have a specific mean vector and variance-covariance matrix. The other algorithm uses a series of additions and subtractions to ensure that data generated from a uniform distribution has a certain mean and variance. Data sets such as these may be beneficial when used for introducing noise in order to mask microdata as a avoidance technique.
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Related Information
WORKING PAPER
Statistical Research Reports and Studies
Page Last Revised - October 28, 2021
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