A Method for Preserving Statistical Distributions Subject to Controlled Tabular Adjustment

Controlled tabular adjustment preserves confidentiality and tabular structure. Quality-preserving controlled tabular adjustment in addition preserves parameters of the distribution of the original (unadjusted) data. Both methods are based on mathematical programming. We introduce a method for preserving the original distribution itself, a fortiori the distributional parameters. The accuracy of the approximation is measured by minimum discrimination information. MDI is computed using an optimal statistical algorithm—iterative proportional fitting.