Open Access
2019 Nonparametric confidence regions for level sets: Statistical properties and geometry
Wanli Qiao, Wolfgang Polonik
Electron. J. Statist. 13(1): 985-1030 (2019). DOI: 10.1214/19-EJS1543

Abstract

This paper studies and critically discusses the construction of nonparametric confidence regions for density level sets. Methodologies based on both vertical variation and horizontal variation are considered. The investigations provide theoretical insight into the behavior of these confidence regions via large sample theory. We also discuss the geometric relationships underlying the construction of horizontal and vertical methods, and how finite sample performance of these confidence regions is influenced by geometric or topological aspects. These discussions are supported by numerical studies.

Citation

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Wanli Qiao. Wolfgang Polonik. "Nonparametric confidence regions for level sets: Statistical properties and geometry." Electron. J. Statist. 13 (1) 985 - 1030, 2019. https://doi.org/10.1214/19-EJS1543

Information

Received: 1 July 2018; Published: 2019
First available in Project Euclid: 30 March 2019

zbMATH: 07056145
MathSciNet: MR3934621
Digital Object Identifier: 10.1214/19-EJS1543

Subjects:
Primary: 62G20
Secondary: 62G05

Keywords: extreme value distribution , integral curves , kernel density estimation , Level sets , nonparametric surface estimation

Vol.13 • No. 1 • 2019
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