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

Chipman, Hugh A.; Hamada, Michael S.

doi:10.1002/qre.2022

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

Abstract

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:

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

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

Publication Date:: 2016-06-02

Research Org.:: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1291219

Report Number(s):: LA-UR-15-26601
Journal ID: ISSN 0748-8017

Grant/Contract Number:: AC52-06NA25396

Resource 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

Country of Publication:: United States

Language:: English

Subject:: 42 ENGINEERING; aliasing; Bayesian; fractional factorial; heredity; hierarchy; sparsity

Citation Formats


                    Chipman, Hugh A., and Hamada, Michael S. Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs.  United States: N. p., 2016. 
Web.  doi:10.1002/qre.2022.

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                    Chipman, Hugh A., & Hamada, Michael S. Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs.  United States.  https://doi.org/10.1002/qre.2022

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                    Chipman, Hugh A., and Hamada, Michael S. Thu .  
"Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs".  United States.  https://doi.org/10.1002/qre.2022.  https://www.osti.gov/servlets/purl/1291219.

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@article{osti_1291219,

  title        = {Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs},

  author       = {Chipman, Hugh A. and Hamada, Michael S.},

  abstractNote = {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.},

  doi          = {10.1002/qre.2022},

  journal      = {Quality and Reliability Engineering International},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2016},

  month        = {6}

}

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https://doi.org/10.1002/qre.2022

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Works referenced in this record:

A Bayesian Analysis of Unreplicated Two-Level Factorials Using Effects Sparsity, Hierarchy, and Heredity
journal, March 2011

Bergquist, Bjarne; Vanhatalo, Erik; Nordenvaad, Magnus Lundberg
Quality Engineering, Vol. 23, Issue 2
DOI: 10.1080/08982112.2011.553760

A Bayesian Variable-Selection Approach for Analyzing Designed Experiments With Complex Aliasing
journal, November 1997

Chipman, H.; Hamada, M.; Wu, C. F. J.
Technometrics, Vol. 39, Issue 4
DOI: 10.1080/00401706.1997.10485156

Bayesian variable selection with related predictors
journal, March 1996

Chipman, Hugh
Canadian Journal of Statistics, Vol. 24, Issue 1
DOI: 10.2307/3315687

Incorporating Prior Information in Optimal Design for Model Selection
journal, May 2007

Bingham, Derek R.; Chipman, Hugh A.
Technometrics, Vol. 49, Issue 2
DOI: 10.1198/004017007000000038

An Analysis for Unreplicated Fractional Factorials
journal, February 1986

Box, George E. P.; Meyer, R. Daniel
Technometrics, Vol. 28, Issue 1
DOI: 10.1080/00401706.1986.10488093

Analysis of Designed Experiments with Complex Aliasing
journal, July 1992

Hamada, M.; Wu, C. F. J.
Journal of Quality Technology, Vol. 24, Issue 3
DOI: 10.1080/00224065.1992.11979383

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Similar Records

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

Abstract

Citation Formats

A Bayesian Analysis of Unreplicated Two-Level Factorials Using Effects Sparsity, Hierarchy, and Heredity journal, March 2011

A Bayesian Variable-Selection Approach for Analyzing Designed Experiments With Complex Aliasing journal, November 1997

Bayesian variable selection with related predictors journal, March 1996

Incorporating Prior Information in Optimal Design for Model Selection journal, May 2007

An Analysis for Unreplicated Fractional Factorials journal, February 1986

Analysis of Designed Experiments with Complex Aliasing journal, July 1992

A Bayesian Analysis of Unreplicated Two-Level Factorials Using Effects Sparsity, Hierarchy, and Heredity
journal, March 2011

A Bayesian Variable-Selection Approach for Analyzing Designed Experiments With Complex Aliasing
journal, November 1997

Bayesian variable selection with related predictors
journal, March 1996

Incorporating Prior Information in Optimal Design for Model Selection
journal, May 2007

An Analysis for Unreplicated Fractional Factorials
journal, February 1986

Analysis of Designed Experiments with Complex Aliasing
journal, July 1992