Quality quandaries: A gentle introduction to Bayesian statistics

Weaver, Brian Phillip; Hamada, Michael Scott

doi:10.1080/08982112.2016.1167220

Title: Quality quandaries: A gentle introduction to Bayesian statistics

Abstract

Here, we provide a gentle introduction to this powerful analysis method that can handle complex data and modeling situations.

Authors:

Weaver, Brian Phillip ^[1]; Hamada, Michael Scott ^[1]

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

Publication Date:: Sat Oct 01 00:00:00 EDT 2016

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

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1291231

Report Number(s):: LA-UR-16-21511
Journal ID: ISSN 0898-2112

Grant/Contract Number:: AC52-06NA25396

Resource Type:: Accepted Manuscript

Journal Name:: Quality Engineering

Additional Journal Information:: Journal Volume: 28; Journal Issue: 4; Journal ID: ISSN 0898-2112

Publisher:: American Society for Quality Control

Country of Publication:: United States

Language:: English

Subject:: 97 MATHEMATICS AND COMPUTING

Citation Formats


                    Weaver, Brian Phillip, and Hamada, Michael Scott. Quality quandaries: A gentle introduction to Bayesian statistics.  United States: N. p., 2016. 
Web.  doi:10.1080/08982112.2016.1167220.

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                    Weaver, Brian Phillip, & Hamada, Michael Scott. Quality quandaries: A gentle introduction to Bayesian statistics.  United States.  https://doi.org/10.1080/08982112.2016.1167220

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                    Weaver, Brian Phillip, and Hamada, Michael Scott. Sat .  
"Quality quandaries: A gentle introduction to Bayesian statistics".  United States.  https://doi.org/10.1080/08982112.2016.1167220.  https://www.osti.gov/servlets/purl/1291231.

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@article{osti_1291231,

  title        = {Quality quandaries: A gentle introduction to Bayesian statistics},

  author       = {Weaver, Brian Phillip and Hamada, Michael Scott},

  abstractNote = {Here, we provide a gentle introduction to this powerful analysis method that can handle complex data and modeling situations.},

  doi          = {10.1080/08982112.2016.1167220},

  journal      = {Quality Engineering},

  number       = 4,

  volume       = 28,

  place        = {United States},

  year         = {Sat Oct 01 00:00:00 EDT 2016},

  month        = {Sat Oct 01 00:00:00 EDT 2016}

}

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https://doi.org/10.1080/08982112.2016.1167220

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Works referenced in this record:

Time Series Analysis With Applications in R
book, January 2008

Cryer, Jonathan D.; Chan, Kung-Sik
Springer Texts in Statistics
DOI: 10.1007/978-0-387-75959-3

Bayesian Data Analysis
book, November 2013

Gelman, Andrew; Carlin, John B.; Stern, Hal S.
DOI: 10.1201/b16018

Works referencing / citing this record:

Analyzing degradation data with a random effects spline regression model
journal, March 2017

Fugate, M. L.; Hamada, M. S.; Weaver, B. P.
Quality Engineering, Vol. 29, Issue 3
DOI: 10.1080/08982112.2017.1307390

Quality quandaries: Predicting a population of curves
journal, August 2017

Fugate, M.; Hamada, M. S.; Weaver, B. P.
Quality Engineering, Vol. 30, Issue 2
DOI: 10.1080/08982112.2017.1417601

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Title: Quality quandaries: A gentle introduction to Bayesian statistics

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Citation Formats

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Time Series Analysis With Applications in R
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