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Title:
Pair correlations preserving model in synthetic data generation
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Mathematics ; Computer software
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Abstract:
The risk of disclosure of confidential information increases by the statistical organizations, due to the large volume of data released to the public. The most common methods of limiting the risk of dicloure are synthetic data genaretion methods. Unfortunately, these methods have a heuristic nature, because they do not have a clear theoretical basis. In this work presented a formal model of synthetic data generation for pair correlation preservation.