Data-driven deconvolution recursive kernel density estimators defined by stochastic approximation method
type: Item
instance of: scholarly article
title: Data-driven deconvolution recursive kernel density estimators defined by stochastic approximation method
zbMATH Open document ID: 1465.62073
author: Yousri Slaoui
published in: Sankhyā. Series A
publication date: 2021-05-03T00:00:00Z
Mathematics Subject Classification ID: 62G07
Mathematics Subject Classification ID: 62L20
Mathematics Subject Classification ID: 65D10
zbMATH DE Number: 7342651
zbMATH Keywords: bandwidth selection
zbMATH Keywords: density estimation
zbMATH Keywords: stochastic approximation algorithm
zbMATH Keywords: deconvolution
zbMATH Keywords: smoothing
zbMATH Keywords: curve fitting
describes a project that uses: decon
MaRDI profile type: Publication
full work available at URL: s13171-019-00182-3
OpenAlex ID: W2992218927
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Wikidata QID: Q126621095
DOI: 10.1007/S13171-019-00182-3
description: scientific article; zbMATH DE number 7342651