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Local continuity of log-concave projection, with applications to estimation under model misspecification

14 February 2020
Rina Foygel Barber
R. Samworth
ArXiv (abs)PDFHTML
Abstract

The log-concave projection is an operator that maps a d-dimensional distribution P to an approximating log-concave density. Prior work by D{\"u}mbgen et al. (2011) establishes that, with suitable metrics on the underlying spaces, this projection is continuous, but not uniformly continuous. In this work we prove a local uniform continuity result for log-concave projection---in particular, establishing that this map is locally H{\"o}lder-(1/4) continuous. A matching lower bound verifies that this exponent cannot be improved. We also examine the implications of this continuity result for the empirical setting---given a sample drawn from a distribution P, we bound the squared Hellinger distance between the log-concave projection of the empirical distribution of the sample, and the log-concave projection of P. In particular, this yields interesting results for the misspecified setting, where P is not itself log-concave.

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