Kernel estimation of density level sets

DOI10.1016/j.jmva.2005.05.004zbMath1085.62039arXivmath/0501221OpenAlexW2009288137MaRDI QIDQ2489497

Benoît Cadre

Publication date: 28 April 2006

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0501221

zbMATH Keywords

Hausdorff measurekernel estimatedensity level sets

Mathematics Subject Classification ID

Density estimation (62G07) Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20)

Related Items (35)

Solution manifold and its statistical applications ⋮ Estimation of density level sets with a given probability content ⋮ Cube root weak convergence of empirical estimators of a density level set ⋮ A data-adaptive method for estimating density level sets under shape conditions ⋮ Asymptotic normality of plug-in level set estimates ⋮ Choosing the most relevant level sets for depicting a sample of densities ⋮ Estimation of level set trees using adaptive partitions ⋮ Generalized density clustering ⋮ Confidence regions for level sets ⋮ Universally consistent estimation of the reach ⋮ Depth level set estimation and associated risk measures ⋮ Level sets semimetrics for probability measures with applications in hypothesis testing ⋮ Data-based decision rules about the convexity of the support of a distribution ⋮ Nonparametric estimation of surface integrals on level sets ⋮ Hypothesis testing based on a vector of statistics ⋮ Asymptotic properties of plug-in level set estimators for right censored data ⋮ Optimal level sets for bivariate density representation ⋮ Exact rates in density support estimation ⋮ Distribution-Free Prediction Sets ⋮ Nonparametric inference via bootstrapping the debiased estimator ⋮ Asymptotics and optimal bandwidth selection for highest density region estimation ⋮ A graph-based estimator of the number of clusters ⋮ Mass volume curves and anomaly ranking ⋮ Detecting relevant changes in the mean of nonstationary processes -- a mass excess approach ⋮ Asymptotics and optimal bandwidth for nonparametric estimation of density level sets ⋮ Nonparametric estimation of regression level sets using kernel plug-in estimator ⋮ Asymptotic confidence regions for density ridges ⋮ Bandwidth selection for kernel density estimators of multivariate level sets and highest density regions ⋮ Posterior contraction and credible regions for level sets ⋮ A comparative simulation study of data-driven methods for estimating density level sets ⋮ Exact asymptotic limit for kernel estimation of regression level sets ⋮ Tree based credible set estimation ⋮ Generalized cluster trees and singular measures ⋮ How to make a neural network say ``Don't know ⋮ PLUG-IN ESTIMATION OF GENERAL LEVEL SETS

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The excess-mass ellipsiod
• On nonparametric estimation of density level sets
• Granulometric smoothing
• A plug-in approach to support estimation
• Total error in a plug-in estimator of level sets.
• Measuring mass concentrations and estimating density contour clusters -- An excess mass approach
• Set estimation and nonparametric detection
• Remarks on Some Nonparametric Estimates of a Density Function
• Excess Mass Estimates and Tests for Multimodality
• Estimation of a Convex Density Contour in Two Dimensions
• A Limit Theorem for Solutions of Inequalities
• Detection of Abnormal Behavior Via Nonparametric Estimation of the Support
• Printer graphics for clustering
• On the Hausdorff distance between a convex set and an interior random convex hull
• Estimating the number of clusters
• Empirical Estimation of Distribution Quantiles of Random Closed Sets
• On boundary estimation
• Rates of convergence for random approximations of convex sets
• Convergence of stochastic processes
• Cluster analysis: a further approach based on density estimation.
• Convergence rates in nonparametric estimation of level sets

This page was built for publication: Kernel estimation of density level sets