In this article, we extend the skew-t data perturbation (STDP) to develop a new statistical disclosure control (SDC) method for data with continuous variables. In this new SDC method, we construct an extended skew-t (EST) copula to release confidential data for third-party usage. Using the EST copula for producing perturbed data, we can incorporate rich statistical information in the perturbed data while preserving the marginal distributions of the data. An advancement of this EST-SDC method is to use a copula distribution, which allows generation of perturbed data from bivariate conditional EST copulas sequentially. We discuss the methodology of EST-SDC and outline some statistical properties derived from copula theories. Simulations and a real data study are included to demonstrate how the EST-SDC method can be applied and to compare with the STDP method. Copyright © 2021 John Wiley & Sons, Ltd.
|Journal||Applied Stochastic Models in Business and Industry|
|Early online date||06 Oct 2021|
|Publication status||Published - Jan 2022|
CitationChu, A. M. Y., Ip, C. Y., Lam, B. S. Y., & So, M. K. P. (2022). Statistical disclosure control for continuous variables using an extended skew-t copula. Applied Stochastic Models in Business and Industry, 38(1), 96-115. doi: 10.1002/asmb.2650
- Business analytics
- Data privacy
- Sensitive data