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Estimation of regression parameters from noise multiplied data

Journal Article


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Abstract


  • This paper considers the scenario that all data entries in a confidentialised unit record file were masked by multiplicative noises, regardless of whether unit records are sensitive or not and regardless of whether the masked variables are dependent or independent variables in the underlying regression analysis. A technique is introduced in this paper to show how to estimate parameters in a regression model, which is originally fitted by unmasked data, based on masked data. Several simulation studies and a real-life data application are presented.

Authors


Publication Date


  • 2012

Citation


  • Lin, Y. & Wise, P. (2012). Estimation of regression parameters from noise multiplied data. Journal of privacy and confidentiality, 4 (2), 61-94.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1755&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/749

Number Of Pages


  • 33

Start Page


  • 61

End Page


  • 94

Volume


  • 4

Issue


  • 2

Place Of Publication


  • http://repository.cmu.edu/jpc/vol4/iss2/4

Abstract


  • This paper considers the scenario that all data entries in a confidentialised unit record file were masked by multiplicative noises, regardless of whether unit records are sensitive or not and regardless of whether the masked variables are dependent or independent variables in the underlying regression analysis. A technique is introduced in this paper to show how to estimate parameters in a regression model, which is originally fitted by unmasked data, based on masked data. Several simulation studies and a real-life data application are presented.

Authors


Publication Date


  • 2012

Citation


  • Lin, Y. & Wise, P. (2012). Estimation of regression parameters from noise multiplied data. Journal of privacy and confidentiality, 4 (2), 61-94.

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1755&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/749

Number Of Pages


  • 33

Start Page


  • 61

End Page


  • 94

Volume


  • 4

Issue


  • 2

Place Of Publication


  • http://repository.cmu.edu/jpc/vol4/iss2/4