Open Access
2016 Asymptotic results for multivariate estimators of the mean density of random closed sets
Federico Camerlenghi, Claudio Macci, Elena Villa
Electron. J. Statist. 10(2): 2066-2096 (2016). DOI: 10.1214/16-EJS1159

Abstract

The problem of the evaluation and estimation of the mean density of random closed sets in $\mathbb{R} ^{d}$ with integer Hausdorff dimension $0<n<d$, is of great interest in many different scientific and technological fields. Among the estimators of the mean density available in literature, the so-called “Minkowski content”-based estimator reveals its benefits in applications in the non-stationary cases. We introduce here a multivariate version of such estimator, and we study its asymptotical properties by means of large and moderate deviation results. In particular we prove that the estimator is strongly consistent and asymptotically Normal. Furthermore we also provide confidence regions for the mean density of the involved random closed set in $m\geq1$ distinct points $x_{1},\ldots,x_{m}\in\mathbb{R} ^{d}$.

Citation

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Federico Camerlenghi. Claudio Macci. Elena Villa. "Asymptotic results for multivariate estimators of the mean density of random closed sets." Electron. J. Statist. 10 (2) 2066 - 2096, 2016. https://doi.org/10.1214/16-EJS1159

Information

Received: 1 January 2016; Published: 2016
First available in Project Euclid: 18 July 2016

zbMATH: 1345.62050
MathSciNet: MR3522669
Digital Object Identifier: 10.1214/16-EJS1159

Subjects:
Primary: 60D05 , 60F10 , 62F12

Keywords: Confidence regions , large deviations , Minkowski content , Moderate deviations , random closed sets

Rights: Copyright © 2016 The Institute of Mathematical Statistics and the Bernoulli Society

Vol.10 • No. 2 • 2016
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