Minimax Estimation of the Volume of a Set Under the Rolling Ball Condition

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Taylor & Francis
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Abstract

We consider the problem of estimating the volume of a compact domain in a Euclidean space based on a uniform sample from the domain. We assume that the domain has a boundary with positive reach. We propose a data-splitting approach to correct the bias of the plug-in estimator based on the sample α-convex hull. We show that this simple estimator achieves a minimax lower bound that we derive. Some numerical experiments corroborate our theoretical findings. Supplementary materials for this article are available online

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This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the American Statistical Association on 2018, available online: http://www.tandfonline.com/10.1080/01621459.2018.1482751

Bibliographic citation

Ery Arias-Castro, Beatriz Pateiro-López & Alberto Rodríguez-Casal (2019) Minimax Estimation of the Volume of a Set Under the Rolling Ball Condition, Journal of the American Statistical Association, 114:527, 1162-1173, DOI: 10.1080/01621459.2018.1482751

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This work was partially supported by the U.S. National Science Foundation (DMS 1513465) and by the Spanish Ministry of Economy and Competitiveness and ERDF funds (MTM2016-76969P)

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© 2018 American Statistical Association