Robust Parameter Designs Constructed from Hadamard Matrices

Yingfu Li () and Kalanka P. Jayalath
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Yingfu Li: College of Science and Engineering, University of Houston—Clear Lake, Houston, TX 77058, USA
Kalanka P. Jayalath: Department of Mathematics and Statistics, University of Houston—Clear Lake, Houston, TX 77058, USA

Stats, 2025, vol. 8, issue 4, 1-14

Abstract: The primary objective of robust parameter design (RPD) is to determine the optimal settings of control factors in a system to minimize response variance while achieving a desirable mean response. This article investigates fractional factorial designs constructed from Hadamard matrices of orders 12, 16, and 20 to meet RPD requirements with minimal runs. For various combinations of control and noise factors, rather than recommending a single “best” design, up to the top ten good candidate designs are identified. All listed designs permit the estimation of all control-by-noise interactions and the main effects of both control and noise factors. Additionally, some nonregular RPDs allow for the estimation of one or two control-by-control interactions, which may be critical for achieving optimal mean response. These results provide practical options for efficient, resource-constrained experiments with economical run sizes.

Keywords: Hadamard matrices; control and noise factors; robust parameter design (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2025
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