Estimation of Regression Parameters from Noise Multiplied Data | Zendy

YanXia Lin | Zendy; Phillip G. Wise | Zendy

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Estimation of Regression Parameters from Noise Multiplied Data

Author(s) -

YanXia Lin,

Phillip G. Wise

Publication year - 2013

Publication title -

journal of privacy and confidentiality

Language(s) - English

Resource type - Journals

ISSN - 2575-8527

DOI - 10.29012/jpc.v4i2.622

Subject(s) - regression , regression analysis , statistics , multiplicative function , computer science , noise (video) , linear regression , unit (ring theory) , data mining , mathematics , artificial intelligence , mathematical analysis , image (mathematics) , mathematics education

This paper considers the scenario that all data entries in a conden- tialised unit record le are 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 tted by unmasked data, based on masked data. Several simulation studies and a real-life data application are presented. AMS Subject Classication: 62D99, 62J99, 62P

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