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Activity Number:
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87
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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Abstract #319085
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Title:
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A Study of Optimal Designs for GLMs Using Particle Swarm Optimization
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Author(s):
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Zhongshen Wang* and John Stufken and Wanchunzi Yu
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Companies:
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Arizona State University and Arizona State University and Arizona State University
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Keywords:
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Complete class approach ;
General equivalence theorem
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Abstract:
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Due to simplicity and effectiveness, Particle Swarm Optimization (PSO) algorithms have recently received considerable attention for finding optimal designs. They can however be inefficient and computationally intensive, especially for high-dimensional problems. We propose a revised version of the traditional algorithm and make suggestions for parameter adjustments. The proposed revision is illustrated by considering generalized linear models with multiple covariates both with and without interaction.
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Authors who are presenting talks have a * after their name.
