Bayesian Variable Selection for Fractional Factorial Experiments with MultilevelCategorical Factors

• Autores: Phil Woodward, Rosalind Walley
• Localización: Journal of quality technology: A quarterly journal of methods applications and related topics, ISSN 0022-4065, Vol. 41, Nº. 3, 2009, págs. 228-240
• Idioma: inglés
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• Resumen

  • The Bayesian approach to fractional factorial experiments is useful for its ability to identify difficult-to-spot interaction effects in experiments with complex aliasing. However, experiments using this approach have consisted either of two-level factors or factors with quantitative levels with priors that cannot be used in experiments with multilevel categorical levels. A simple multivariate normal prior is presented that is a natural extension of the prior used for two-level factors. Its effectiveness is demonstrated by reanalyzing two multilevel factorial experiments with complex aliasing.