Differential Privacy Applications to Bayesian and Linear Mixed Model Estimation
نویسندگان
چکیده
منابع مشابه
Differential Privacy Applications to Bayesian and Linear Mixed Model Estimation
We consider a particular maximum likelihood estimator (MLE) and a computationally-intensive Bayesian method for differentially private estimation of the linear mixed-effects model (LMM) with normal random errors. The LMM is important because it is used in small area estimation and detailed industry tabulations that present significant challenges for confidentiality protection of the underlying ...
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ژورنال
عنوان ژورنال: Journal of Privacy and Confidentiality
سال: 2013
ISSN: 2575-8527
DOI: 10.29012/jpc.v5i1.627