Abstract
Complex systems such as large-scale computer simulation models typically involve a large number of factors. When investigating such a system, screening experiments are often used to sift through these factors to identify a subgroup of factors that most significantly influence the interested response.
Keywords
Experiment Design, Lasso, Model Selection, Sign Correctness, Simulation, Supersaturated Design
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Industrial Engineering
First Advisor
Hong Wan
Second Advisor
Yu Zhu
Committee Member 1
Bruce A. Craig
Committee Member 2
Lu Liu
Date of Award
January 2015
Recommended Citation
XING, DADI, "LASSO-OPTIMAL SUPERSATURATED DESIGN AND ANALYSIS FOR FACTOR SCREENING IN SIMULATION EXPERIMENTS" (2015). Open Access Dissertations. 1327.
https://docs.lib.purdue.edu/open_access_dissertations/1327
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