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A Bayesian Analysis of Unreplicated Two-Level Factorials Using Effects Sparsity, Hierarchy, and Heredity

Summary: [This abstract is based on the authors' abstract.] A Bayesian procedure for calculating posterior probabilities of active effects for unreplicated two-level factorials is proposed. A literature survey provides individual prior probabilities, which are used to calculate posterior probabilities in a three-step procedure considering sparsity, hierarchy, and heredity. The approach is demonstrated by reanalyzing previous experiments from the literature.

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  • Topics: Statistics
  • Keywords: Bayesian methods, Engineering, Markov chains, Monte Carlo methods, Posterior, Probability, Unreplicated factorial experiment
  • Author: Bergquist, Bjarne; Vanhatalo, Erik; Nordenvaad, Magnus Lundberg;
  • Journal: Quality Engineering