ERA

Analytics

Share

Export to: EndNote  |  Zotero  |  Mendeley

Communities

This file is in the following communities:

Collections

This file is in the following collections:

Comparison of Three Methods of Generating Robust Statistical Designs Open Access

Descriptions

Other title
Subject/Keyword

Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Yu, Dengdeng
Supervisor and department
Wiens, Douglas (Mathematical and Statistical Sciences)
Examining committee member and department
Chough, Keumhee Carriere (Mathematical and Statistical Sciences)
Frei, Christoph (Mathematical and Statistical Sciences)
Wiens, Douglas (Mathematical and Statistical Sciences)
Kong, Linglong (Mathematical and Statistical Sciences)
Department
Department of Mathematical and Statistical Sciences
Specialization
Statistics
Date accepted
2013-09-29T16:45:09Z
2013-11
Degree
Master of Science
Degree level
Master's
Abstract
This thesis deals with the problem proposed by Ye and Zhou (2007): Is a Q-optimal minimax design still symmetric if the requirement of $\int_\chi xm(x)dx = 0$ is removed? We have shown that for the simple linear regression, considering only the variance, a Q-optimal minimax design is necessarily symmetric; we have also made an attempt of addressing the symmetry problem considering only the bias which is much more difficult to achieve. However, the numerical results using three different algorithms, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Expected Improvement Algorithm (EIA), indicate that the claim is true. We have also applied the three algorithm on a non-linear cases correspondingly and make the comparison.
Language
English
DOI
doi:10.7939/R3JH3D872
Rights
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication

File Details

Date Modified
2014-04-24T22:44:12.801+00:00
Audit Status
Audits have not yet been run on this file.
Characterization
File format: pdf (Portable Document Format)
Mime type: application/pdf
File size: 443491