A Bayesian approach to multivariate measurement system assessment

Hamada, Michael Scott

Title: A Bayesian approach to multivariate measurement system assessment

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Abstract

This article considers system assessment for multivariate measurements and presents a Bayesian approach to analyzing gauge R&R study data. The evaluation of variances for univariate measurement becomes the evaluation of covariance matrices for multivariate measurements. The Bayesian approach ensures positive definite estimates of the covariance matrices and easily provides their uncertainty. Furthermore, various measurement system assessment criteria are easily evaluated. The approach is illustrated with data from a real gauge R&R study as well as simulated data.

Authors:

Hamada, Michael Scott ^[1]

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

Publication Date:: Fri Jul 01 00:00:00 EDT 2016

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

Sponsoring Org.:: USDOE

OSTI Identifier:: 1331257

Report Number(s):: LA-UR-14-28562
Journal ID: ISSN 0022-4065

Grant/Contract Number:: AC52-06NA25396

Resource Type:: Accepted Manuscript

Journal Name:: Journal of Quality Technology

Additional Journal Information:: Journal Volume: 48; Journal Issue: 3; Journal ID: ISSN 0022-4065

Publisher:: American Society for Quality (ASQ)

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING; gauge R & R study; Markov-chain Monte Carlo; multivariate normal distribution; random effects; repeatability; reproducibility; uncertainty; variance components; scaled inverse Wishart Prior Distribution

Citation Formats


                    Hamada, Michael Scott. A Bayesian approach to multivariate measurement system assessment.  United States: N. p., 2016. 
Web.

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                    Hamada, Michael Scott. A Bayesian approach to multivariate measurement system assessment.  United States.

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                    Hamada, Michael Scott. Fri .  
"A Bayesian approach to multivariate measurement system assessment".  United States.  https://www.osti.gov/servlets/purl/1331257.

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@article{osti_1331257,

  title        = {A Bayesian approach to multivariate measurement system assessment},

  author       = {Hamada, Michael Scott},

  abstractNote = {This article considers system assessment for multivariate measurements and presents a Bayesian approach to analyzing gauge R&R study data. The evaluation of variances for univariate measurement becomes the evaluation of covariance matrices for multivariate measurements. The Bayesian approach ensures positive definite estimates of the covariance matrices and easily provides their uncertainty. Furthermore, various measurement system assessment criteria are easily evaluated. The approach is illustrated with data from a real gauge R&R study as well as simulated data.},

  doi          = {},

  journal      = {Journal of Quality Technology},

  number       = 3,

  volume       = 48,

  place        = {United States},

  year         = {Fri Jul 01 00:00:00 EDT 2016},

  month        = {Fri Jul 01 00:00:00 EDT 2016}

}

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