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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
- 4Quantile regression
- 1Asymmetric Laplace distribution
- 1Average quantile regression
- 1B-spline approximations
- 1Bayesian statistics
- 1Composite quantile regression
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Computation in quantile and composite quantile regression models with or without regularization
DownloadFall 2015
Quantile, composite quantile regression with or without regularization have been widely studied and applied in the high-dimensional model estimation and variable selections. Although the theoretical aspect has been well established, the lack of efficient computation methods and publicly available...
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Fall 2016
There is an increasing interest in extreme value analysis for financial and climate data. Various statistical methods have been developed for estimating extreme value dependence in time series data sets and the field continues to grow. In this work we consider four statistical methods for...
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Fall 2014
Quantile regression supplements the ordinary least squares regression and provides a complete view of a relationship between a response variable and a set of covariates. The quantile regression model does not assume any particular error distribution. It is estimated by minimizing an asymmetric...
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Fall 2014
This thesis develops an efficient quantile-adaptive framework for linear and nonlinear variable screening with high-dimensional heterogeneous data. Inspired by the success of various variable screening methods, especially in the quantile-adaptive framework, we develop a more efficient variable...