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Using Bayesian Variable Selection to Analyze Regular Resolution IV Two‐level Fractional Factorial Designs
Author(s) -
Chipman Hugh A.,
Hamada Michael S.
Publication year - 2017
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.2022
Subject(s) - fractional factorial design , selection (genetic algorithm) , bayesian probability , mathematics , factorial experiment , variable (mathematics) , statistics , aliasing , feature selection , computer science , artificial intelligence , mathematical analysis , undersampling
Regular two‐level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. In this article, we show how Bayesian variable selection can be used to analyze experiments that use such designs. Bayesian variable selection naturally incorporates heredity in addition to sparsity and hierarchy. This prior information is used to identify the most likely combinations of active terms. The method is demonstrated on simulated and real experiments. Copyright © 2016 John Wiley & Sons, Ltd.