Class
Article
College
College of Science
Department
Mathematics and Statistics Department
Faculty Mentor
Stephen J. Walsh
Presentation Type
Poster Presentation
Abstract
In 1935, Ronald Fisher published The Design of Experiments, establishing classical designs for various types of experiments. With the rise of computing power came optimal design, where statisticians can better customize designs according to the needs of the researchers running the experiment. This research focuses on generating optimal MaxMin space-filling designs with particle swarm optimization using various distance metrics (Manhattan, Euclidean, etc). Interestingly, changing the distance metric in the objective function had a minimal effect on the design, except for Aitchison geometry on the simplex. Space-filling designs are optimal for supporting high-order models with only a small sacrifice in prediction variance when compared to classical designs.
Location
Logan, UT
Start Date
4-12-2023 11:30 AM
End Date
4-12-2023 12:30 PM
Included in
Generating Optimal Space-Filling Designs With Particle Swarm Optimization
Logan, UT
In 1935, Ronald Fisher published The Design of Experiments, establishing classical designs for various types of experiments. With the rise of computing power came optimal design, where statisticians can better customize designs according to the needs of the researchers running the experiment. This research focuses on generating optimal MaxMin space-filling designs with particle swarm optimization using various distance metrics (Manhattan, Euclidean, etc). Interestingly, changing the distance metric in the objective function had a minimal effect on the design, except for Aitchison geometry on the simplex. Space-filling designs are optimal for supporting high-order models with only a small sacrifice in prediction variance when compared to classical designs.