Bayesian simultaneous prediction intervals and bounds for a finite population
Abstract
Simultaneous prediction intervals and bounds provide a statistical characterization of a proportion of a finite population. In this article we consider these predictions from a Bayesian inferential approach and different ways to evaluate them including simulation.
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)
- OSTI Identifier:
- 1597344
- Report Number(s):
- LA-UR-19-24501
Journal ID: ISSN 0898-2112
- Grant/Contract Number:
- 89233218CNA000001
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Quality Engineering
- Additional Journal Information:
- Journal Volume: 32; Journal Issue: 2; Journal ID: ISSN 0898-2112
- Publisher:
- American Society for Quality Control
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 01 COAL, LIGNITE, AND PEAT
Citation Formats
Hamada, Michael Scott, and Weaver, Brian Phillip. Bayesian simultaneous prediction intervals and bounds for a finite population. United States: N. p., 2019.
Web. doi:10.1080/08982112.2019.1656811.
Hamada, Michael Scott, & Weaver, Brian Phillip. Bayesian simultaneous prediction intervals and bounds for a finite population. United States. https://doi.org/10.1080/08982112.2019.1656811
Hamada, Michael Scott, and Weaver, Brian Phillip. Tue .
"Bayesian simultaneous prediction intervals and bounds for a finite population". United States. https://doi.org/10.1080/08982112.2019.1656811. https://www.osti.gov/servlets/purl/1597344.
@article{osti_1597344,
title = {Bayesian simultaneous prediction intervals and bounds for a finite population},
author = {Hamada, Michael Scott and Weaver, Brian Phillip},
abstractNote = {Simultaneous prediction intervals and bounds provide a statistical characterization of a proportion of a finite population. In this article we consider these predictions from a Bayesian inferential approach and different ways to evaluate them including simulation.},
doi = {10.1080/08982112.2019.1656811},
journal = {Quality Engineering},
number = 2,
volume = 32,
place = {United States},
year = {2019},
month = {12}
}
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Works referenced in this record:
Bayesian Prediction Intervals and Their Relationship to Tolerance Intervals
journal, November 2004
- Hamada, Michael; Johnson, Valen; Moore, Leslie M.
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Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
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- Gelman, Andrew
- Bayesian Analysis, Vol. 1, Issue 3