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Three key functionalities are present. It is able to mask confidential data using multiplicative noise. It is able to unmask this data while still preserving confidentiality. It is able to calculate the numerical joint density function of the original data from the unmasked data, as well as obtaining a sample from the marginal density functions of the unmasked data. The final results are a reasonable approximation to the original data for the purposes of analysis (Lin et al. (2018) <http://www.tdp.cat/issues16/abs.a271a17.php>).
Package details 


Author  YanXia Lin [aut, cre], Luke Mazur [aut, cre], Jordan Morris [ctb] 
Maintainer  Luke Mazur <lm810@uowmail.edu.au> 
License  GPL2 
Version  1.0 
Package repository  View on CRAN 
Installation 
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