A note on the choice of the smoothing parameter in the kernel dinsity estimate

Among different density estimation procedures, the kernel density estimation has attracted the most attention. In this paper, the choices for smoothing parameter is discussed when the widely used Gaussian kernel is used in implementing the kernel density estimate. A simulation study is conducted fro...

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Библиографические подробности
Главные авторы:	Froelich, Daniel F., Rahman, Mezbahur
Формат:	Статья
Язык:	English
Опубликовано:	BRAC University 2010
Предметы:	Bias Mean integrated squared error Newton Rapson Method
Online-ссылка:	http://hdl.handle.net/10361/451

id	10361-451
record_format	dspace
spelling	10361-4512019-09-29T05:47:54Z A note on the choice of the smoothing parameter in the kernel dinsity estimate Froelich, Daniel F. Rahman, Mezbahur Bias Mean integrated squared error Newton Rapson Method Among different density estimation procedures, the kernel density estimation has attracted the most attention. In this paper, the choices for smoothing parameter is discussed when the widely used Gaussian kernel is used in implementing the kernel density estimate. A simulation study is conducted from several mixtures of normal distributions covering a wide range of distributional shapes. 2010-10-11T06:08:23Z 2010-10-11T06:08:23Z 2009 Article http://hdl.handle.net/10361/451 en BRAC University Journal, BRAC University;Vol.6, No.1,pp. 59-68 application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Bias Mean integrated squared error Newton Rapson Method
spellingShingle	Bias Mean integrated squared error Newton Rapson Method Froelich, Daniel F. Rahman, Mezbahur A note on the choice of the smoothing parameter in the kernel dinsity estimate
description	Among different density estimation procedures, the kernel density estimation has attracted the most attention. In this paper, the choices for smoothing parameter is discussed when the widely used Gaussian kernel is used in implementing the kernel density estimate. A simulation study is conducted from several mixtures of normal distributions covering a wide range of distributional shapes.
format	Article
author	Froelich, Daniel F. Rahman, Mezbahur
author_facet	Froelich, Daniel F. Rahman, Mezbahur
author_sort	Froelich, Daniel F.
title	A note on the choice of the smoothing parameter in the kernel dinsity estimate
title_short	A note on the choice of the smoothing parameter in the kernel dinsity estimate
title_full	A note on the choice of the smoothing parameter in the kernel dinsity estimate
title_fullStr	A note on the choice of the smoothing parameter in the kernel dinsity estimate
title_full_unstemmed	A note on the choice of the smoothing parameter in the kernel dinsity estimate
title_sort	note on the choice of the smoothing parameter in the kernel dinsity estimate
publisher	BRAC University
publishDate	2010
url	http://hdl.handle.net/10361/451
work_keys_str_mv	AT froelichdanielf anoteonthechoiceofthesmoothingparameterinthekerneldinsityestimate AT rahmanmezbahur anoteonthechoiceofthesmoothingparameterinthekerneldinsityestimate AT froelichdanielf noteonthechoiceofthesmoothingparameterinthekerneldinsityestimate AT rahmanmezbahur noteonthechoiceofthesmoothingparameterinthekerneldinsityestimate
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A note on the choice of the smoothing parameter in the kernel dinsity estimate

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