A mixture- based framework for nonparametric density estimation

The primary goal of this thesis is to provide a mixture-based framework for nonparametric density estimation. This framework advocates the use of a mixture model with a nonparametric mixing distribution to approximate the distribution of the data. The implementation of a mixture-based nonparametric...

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Main Author:	Chew-Seng, Chee
Format:	Thesis
Language:	English
Subjects:	QA 278.8 .C4 2011 Tesis University of Auckland 2011 Nonparametric statistics > Research
Online Access:	http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/1621/1/QA%20278.8%20.C4%202011%20Abstract.pdf http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/1621/2/QA%20278.8%20.C4%202011%20FullText.pdf
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id	my-umt-ir.-1621
record_format	uketd_dc
spelling	my-umt-ir.-16212012-07-23T07:04:33Z A mixture- based framework for nonparametric density estimation Chew-Seng, Chee The primary goal of this thesis is to provide a mixture-based framework for nonparametric density estimation. This framework advocates the use of a mixture model with a nonparametric mixing distribution to approximate the distribution of the data. The implementation of a mixture-based nonparametric density estimator generally requires the specification of parameters in a mixture model and the choice of the bandwidth parameter. Consequently, a nonparametric methodology consisting of both the estimation and selection steps is described. New Zealand: University of Auckland 2011 Thesis en http://hdl.handle.net/123456789/1621 http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/1621/1/QA%20278.8%20.C4%202011%20Abstract.pdf d2fe301efd0ee61ad712e66c0f7e2acb http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/1621/2/QA%20278.8%20.C4%202011%20FullText.pdf 9242dc34de7c351fdaddc163cc8b3f44 http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/1621/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 QA 278.8 .C4 2011 Chew-Seng, Chee Tesis University of Auckland 2011 Nonparametric statistics -- Research
institution	Universiti Malaysia Terengganu
collection	UMT Repository System
language	English
topic	QA 278.8 .C4 2011 QA 278.8 .C4 2011 Tesis University of Auckland 2011 Nonparametric statistics -- Research
spellingShingle	QA 278.8 .C4 2011 QA 278.8 .C4 2011 Tesis University of Auckland 2011 Nonparametric statistics -- Research Chew-Seng, Chee A mixture- based framework for nonparametric density estimation
description	The primary goal of this thesis is to provide a mixture-based framework for nonparametric density estimation. This framework advocates the use of a mixture model with a nonparametric mixing distribution to approximate the distribution of the data. The implementation of a mixture-based nonparametric density estimator generally requires the specification of parameters in a mixture model and the choice of the bandwidth parameter. Consequently, a nonparametric methodology consisting of both the estimation and selection steps is described.
format	Thesis
author	Chew-Seng, Chee
author_facet	Chew-Seng, Chee
author_sort	Chew-Seng, Chee
title	A mixture- based framework for nonparametric density estimation
title_short	A mixture- based framework for nonparametric density estimation
title_full	A mixture- based framework for nonparametric density estimation
title_fullStr	A mixture- based framework for nonparametric density estimation
title_full_unstemmed	A mixture- based framework for nonparametric density estimation
title_sort	mixture- based framework for nonparametric density estimation
granting_institution	New Zealand: University of Auckland
url	http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/1621/1/QA%20278.8%20.C4%202011%20Abstract.pdf http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/1621/2/QA%20278.8%20.C4%202011%20FullText.pdf
_version_	1747835776959250432

A mixture- based framework for nonparametric density estimation

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