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Differentially Private Kolmogorov-Smirnov-Type Tests. (arXiv:2208.06236v1 [stat.ME])
Aug. 15, 2022, 1:20 a.m. | Jordan Awan, Yue Wang
cs.CR updates on arXiv.org arxiv.org
The test statistics for many nonparametric hypothesis tests can be expressed
in terms of a pseudo-metric applied to the empirical cumulative distribution
function (ecdf), such as Kolmogorov-Smirnov, Kuiper, Cram\'er-von Mises, and
Wasserstein. These test statistics can be used to test goodness-of-fit,
two-samples, paired data, or symmetry. For the design of differentially private
(DP) versions of these tests, we show that test statistics of this form have
small sensitivity, requiring a minimal amount of noise to achieve DP. The tests
are …
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