Invariance principles for deconvolving kernel density estimation for stationary sequences of random variables
type: Item
instance of: scholarly article
title: Invariance principles for deconvolving kernel density estimation for stationary sequences of random variables
zbMATH Open document ID: 0952.62030
DOI: 10.1016/S0378-3758(99)00162-7
published in: Journal of Statistical Planning and Inference
publication date: 2000-04-27T00:00:00Z
Mathematics Subject Classification ID: 62G07
Mathematics Subject Classification ID: 60F17
Mathematics Subject Classification ID: 62M09
Mathematics Subject Classification ID: 62G30
Mathematics Subject Classification ID: 62G20
zbMATH DE Number: 1436955
zbMATH Keywords: kernel density estimators
zbMATH Keywords: deconvolution
zbMATH Keywords: Fourier transformation
zbMATH Keywords: weak convergence
zbMATH Keywords: strong convergence
author: Stergios Fotopoulos
MaRDI profile type: Publication
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Wikidata QID: Q126573640
full work available at URL: s0378-3758(99)00162-7
OpenAlex ID: W1978687910
description: scientific article; zbMATH DE number 1436955