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Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 477Department of Mathematical and Statistical Sciences
- 2Department of Biological Sciences
- 2Department of Mechanical Engineering
- 1Department of Civil and Environmental Engineering
- 1Department of Computing Science
- 1Department of Public Health Sciences
- 7Frei, Christoph (Mathematical and Statistical Sciences)
- 7Hillen, Thomas (Mathematical and Statistical Sciences)
- 7Kong, Linglong (Mathematical and Statistical Sciences)
- 7Lewis, Mark (Mathematical and Statistical Sciences)
- 6Han, Bin (Mathematical and Statistical Sciences)
- 6Kashlak, Adam (Mathematical and Statistical Sciences)
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Fall 2016
We study penalized fitting strategies aimed at sparse model selection of models satisfying certain hierarchical restrictions, in linear models arising from factorial experiments. After discussing various merits of existing approaches, we propose a modification and generalization of the approach...
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Spring 2011
A flag of a finite dimensional vector space V is a nested sequence of subspaces of V . The symplectic group of V acts on the set of flags of V . We classify the orbits of this action by defining the incidence matrix of a flag of V and show- ing that two flags are in the same orbit precisely when...
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Fully sequential monitoring of longitudinal trials using sequential ranks, with applications to an orthodontics study
DownloadFall 2009
This thesis explores the application of fully sequential methods for the analysis of longitudinal clinical trial data. A new nonparametric approach will be developed, using sequential ranks, for the comparison of several treatment groups. Sequential ranking is an alternative to ranking by the...
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Fall 2021
The Covid pandemic has lasted for over a year influencing everyone's physical and emotional well-beings. Our work is aimed at exploring the capability of various types of functional data clustering methods on the complex Covid data. We collect the Covid data from the Our World in Data website,...
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Fall 2011
Functional data analysis (FDA) is a fast-growing area in statistics with the aim of estimating a set of related functions or curves rather than focusing on a single entity, like estimating a point, as in classical statistics. FDA has a wide range of applications in different fields such as...
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Fall 2020
Real Time Cell Analysis (RTCA) technology is used to monitor cellular changes continuously over the entire exposure period to chemicals. In RTCA system, chemicals with di erent concen- trations are applied and time-dependent concentration response curves (TCRCs) are generated. In this thesis, we...
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Fall 2023
$G$-structures on fusion categories have been shown to be an important tool to understand orbifolds of vertex operator algebras \cite{Kirillov}\cite{Gcrossedmuger}\cite{Orbifold_Paper}. We continue to develop this idea by generalizing Eilenberg-Maclane's notion of an Abelian $3$-cocycle to...
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Fall 2021
This thesis proposes a novel Gaussian copula function-on-scalar regression, which is more flexible to characterize the relationship between functional or image response and scalar predictors and is able to relax the linear assumption in traditional function-on-scalar linear regression. Estimation...