eprintid: 48403
rev_number: 13
eprint_status: archive
userid: 1482
importid: 105
dir: disk0/00/04/84/03
datestamp: 2023-11-29 13:44:36
lastmod: 2024-11-08 15:11:44
status_changed: 2024-11-08 15:11:44
type: article
metadata_visibility: show
creators_name: Shirazi, Esmaeil
creators_name: Faugeras, Olivier Paul
creators_id: shirazi.esmaeel@gmail.com
creators_id: olivier.faugeras@tse-fr.eu
creators_idrefppn: 135534518
creators_affiliation: Toulouse School of Economics
creators_halaffid: 1002422
title: A new wavelet-based estimation of conditional density via block threshold method
ispublished: pub
subjects: subjects_ECO
abstract: A new wavelet-based estimator of the conditional density is investigated. The estimator is constructed by combining a special ratio technique and applying a non negative estimator to the density function in the denominator. We used a wavelet shrinkage technique to find an adaptive estimator for this problem. In particular, a block thresholding estimator is proposed, and we prove that it enjoys powerful mean integrated squared error properties over Besov balls. Moreover, it is shown that convergence rates for the mean integrated squared error (MISE) of the adaptive estimator are optimal under some mild assumptions. Finally, a numerical example has been considered to illustrate the performance of the estimator.
date: 2023-11
date_type: published
publisher: Taylor & Francis
id_number: 10.1080/03610926.2023.2279917
official_url: http://tse-fr.eu/pub/128731
faculty: tse
divisions: tse
language: en
has_fulltext: FALSE
doi: 10.1080/03610926.2023.2279917
view_date_year: 2023
full_text_status: none
publication: Communications in Statistics: Theory and Method
place_of_pub: New York, NY
refereed: TRUE
issn: 0361-0926
oai_identifier: oai:tse-fr.eu:128731
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oai_lastmod: 2024-07-26T08:53:11Z
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site: ut1
hal_id: hal-04315135
hal_passwd: ye4jr3uf
hal_version: 1
hal_url: https://hal.science/hal-04315135
citation:   Shirazi, Esmaeil and Faugeras, Olivier Paul <https://www.idref.fr/135534518>  (2023) A new wavelet-based estimation of conditional density via block threshold method.    Communications in Statistics: Theory and Method.