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Permanent link (DOI): https://doi.org/10.7939/R3N03W

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Non parametric density estimation via regularization Open Access

Descriptions

Other title
Subject/Keyword
Non parametric density estimation via regularization
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Lin, Mu
Supervisor and department
Mizera, Ivan (Department of Mathematical and Statistical Sciences)
Examining committee member and department
Li, Pengfei (Department of Mathematical and Statistical Sciences)
Karunamuni, Rohana (Department of Mathematical and Statistical Sciences)
Leuangthong, Oy (Department of Civil and Environmental Engineering)
Department
Department of Mathematical and Statistical Sciences
Specialization

Date accepted
2009-10-01T20:39:38Z
Graduation date
2009-11
Degree
Master of Science
Degree level
Master's
Abstract
The thesis aims at showing some important methods, theories and applications about non-parametric density estimation via regularization in univariate setting. It gives a brief introduction to non-parametric density estimation, and discuss several well-known methods, for example, histogram and kernel methods. Regularized methods with penalization and shape constraints are the focus of the thesis. Maximum entropy density estimation is introduced and the relationship between taut string and maximum entropy density estimation is explored. Furthermore, the dual and primal theories are discussed and some theoretical proofs corresponding to quasi-concave density estimation are presented. Different the numerical methods of non-parametric density estimation with regularization are classified and compared. Finally, a real data experiment will also be discussed in the last part of the thesis.
Language
English
DOI
doi:10.7939/R3N03W
Rights
License granted by Mu Lin (linmu@math.ualberta.ca) on 2009-09-30T21:03:07Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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