Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs

Journal Article · 02 June 2016 · Quality and Reliability Engineering International

DOI: https://doi.org/10.1002/qre.2022 · OSTI ID:1291219

Chipman, Hugh A. ^[1]; Hamada, Michael S. ^[2]

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1. Acadia Univ., Wolfville, NS (Canada)
2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Regular two-level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. Here, we show how Bayesian variable selection can be used to analyze experiments that use such designs. In addition to sparsity and hierarchy, Bayesian variable selection naturally incorporates heredity . This prior information is used to identify the most likely combinations of active terms. We also demonstrate the method on simulated and real experiments.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC52-06NA25396
• OSTI ID: 1291219
• Report Number(s): LA-UR-15-26601
• Journal Information: Quality and Reliability Engineering International, Journal Name: Quality and Reliability Engineering International; ISSN 0748-8017
• Publisher: WileyCopyright Statement
• Country of Publication: United States
• Language: English