Deconvolving multidimensional density from partially contaminated observations
type: Item
instance of: scholarly article
title: Deconvolving multidimensional density from partially contaminated observations
zbMATH Open document ID: 1011.62039
DOI: 10.1016/S0378-3758(01)00238-5
author: Ming Yuan
author: Jiaqin Chen
published in: Journal of Statistical Planning and Inference
publication date: 2002-06-16T00:00:00Z
Mathematics Subject Classification ID: 62G07
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 62G20
zbMATH DE Number: 1756411
zbMATH Keywords: strong mixing
zbMATH Keywords: kernel density estimation
zbMATH Keywords: partial contamination
zbMATH Keywords: deconvolution
zbMATH Keywords: mean squared errors
zbMATH Keywords: strong consistency
zbMATH Keywords: asymptotic normality
MaRDI profile type: Publication
cites work: Q4836494
cites work: Nonparametric statistics for stochastic processes
cites work: Approximation theorems for strongly mixing random variables
cites work: Optimal Rates of Convergence for Deconvolving a Density
cites work: On the optimal rates of convergence for nonparametric deconvolution problems
cites work: Q4839949
cites work: Deconvolving a density from partially contaminated observations
cites work: A consistent nonparametric density estimator for the deconvolution problem
cites work: Strong consistency and rates for deconvolution of multivariate densities of stationary processes
cites work: Asymptotic normality for deconvolution estimators of multivariate densities of stationary processes
cites work: Rates of convergence of some estimators in a class of deconvolution problems
cites work: Deconvolving kernel density estimators
cites work: Some Limit Theorems for Random Functions. I
cites work: Fourier methods for estimating mixing densities and distributions
Wikidata QID: Q126572570
description: scientific article; zbMATH DE number 1756411