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arxiv: 1802.01152 · v1 · pith:YNXCISQHnew · submitted 2018-02-04 · 📊 stat.ME · cs.CG· stat.ML

Testing to distinguish measures on metric spaces

classification 📊 stat.ME cs.CGstat.ML
keywords metricdatamathbbproblemspacestestanalysisdetermining
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We study the problem of distinguishing between two distributions on a metric space; i.e., given metric measure spaces $({\mathbb X}, d, \mu_1)$ and $({\mathbb X}, d, \mu_2)$, we are interested in the problem of determining from finite data whether or not $\mu_1$ is $\mu_2$. The key is to use pairwise distances between observations and, employing a reconstruction theorem of Gromov, we can perform such a test using a two sample Kolmogorov--Smirnov test. A real analysis using phylogenetic trees and flu data is presented.

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