Inference about a Binomial Proportion under Privacy Protection

Written by:
RRS2026-01

Abstract

In this paper we consider the inferential problem for a Binomial proportion in situations when the exact number of units possessing an attribute under consideration is unavailable due to privacy reasons; however a synthesized version of this number is available. The inference problem is addressed under three types of available information: noise added version and plug-in sampling based and posterior sampling based data. A comparison of the three modes of data source is made based on inferential accuracy and a measure of privacy.

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