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Journal Articles Electronic Journal of Statistics Year : 2019

A statistical test of isomorphism between metric-measure spaces using the distance-to-a-measure signature

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Abstract

We introduce the notion of DTM-signature, a measure on R that can be associated to any metric-measure space. This signature is based on the function distance to a measure (DTM) introduced in 2009 by Chazal, Cohen-Steiner and Mérigot. It leads to a pseudo-metric between metric-measure spaces, that is bounded above by the Gromov-Wasserstein distance. This pseudo-metric is used to build a statistical test of isomorphism between two metric-measure spaces, from the observation of two N-samples. The test is based on subsampling methods and comes with theoretical guarantees. It is proven to be of the correct level asymptotically. Also, when the measures are supported on compact subsets of R^d, rates of convergence are derived for the L1-Wasserstein distance between the distribution of the test statistic and its subsampling approximation. These rates depend on some parameter \rho> 1. In addition, we prove that the power is bounded above by exp(−CN^(1/ \rho)), with C proportional to the square of the aforementioned pseudo-metric between the metric-measure spaces. Under some geometrical assumptions, we also derive lower bounds for this pseudo-metric. An algorithm is proposed for the implementation of this statistical test, and its performance is compared to the performance of other methods through numerical experiments.
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Dates and versions

hal-01426331 , version 1 (04-01-2017)
hal-01426331 , version 2 (09-02-2017)
hal-01426331 , version 3 (20-02-2019)

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Claire Brécheteau. A statistical test of isomorphism between metric-measure spaces using the distance-to-a-measure signature. Electronic Journal of Statistics , In press, ⟨10.1214/154957804100000000⟩. ⟨hal-01426331v3⟩
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