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This content will become publicly available on June 2, 2017

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

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.
Authors:
 [1] ;  [2]
  1. Acadia Univ., Wolfville, NS (Canada)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
OSTI Identifier:
1291219
Report Number(s):
LA-UR--15-26601
Journal ID: ISSN 0748-8017
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
Quality and Reliability Engineering International
Additional Journal Information:
Journal Name: Quality and Reliability Engineering International; Journal ID: ISSN 0748-8017
Publisher:
Wiley
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
42 ENGINEERING aliasing; Bayesian; fractional factorial; heredity; hierarchy; sparsity