A note on the Bayesian analysis of experiments with correlated multiple responses using a matrixlogarithmic covariance model
Abstract
In the literature, analysis of multiple responses from experiments with replicates has modeled the covariance matrix directly as linear models of the transformed variances and correlations, i.e., covariance modeling. This article considers models based on the matrix logarithm of the covariance matrix. This socalled logcovariance modeling is illustrated with data from actual experiments and compared with the traditional covariance modeling.
 Authors:

 Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
 Soochow Univ., Suzhou (China)
 Publication Date:
 Research Org.:
 Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
 Sponsoring Org.:
 USDOE National Nuclear Security Administration (NNSA)
 OSTI Identifier:
 1558204
 Report Number(s):
 LAUR1827818
Journal ID: ISSN 07488017
 Grant/Contract Number:
 89233218CNA000001
 Resource Type:
 Accepted Manuscript
 Journal Name:
 Quality and Reliability Engineering International
 Additional Journal Information:
 Journal Volume: 35; Journal Issue: 7; Journal ID: ISSN 07488017
 Publisher:
 Wiley
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS AND COMPUTING
Citation Formats
Hamada, Michael S., Jaramillo, Brandon M., and Chiao, Chih‐Hua. A note on the Bayesian analysis of experiments with correlated multiple responses using a matrixlogarithmic covariance model. United States: N. p., 2019.
Web. https://doi.org/10.1002/qre.2540.
Hamada, Michael S., Jaramillo, Brandon M., & Chiao, Chih‐Hua. A note on the Bayesian analysis of experiments with correlated multiple responses using a matrixlogarithmic covariance model. United States. https://doi.org/10.1002/qre.2540
Hamada, Michael S., Jaramillo, Brandon M., and Chiao, Chih‐Hua. Tue .
"A note on the Bayesian analysis of experiments with correlated multiple responses using a matrixlogarithmic covariance model". United States. https://doi.org/10.1002/qre.2540. https://www.osti.gov/servlets/purl/1558204.
@article{osti_1558204,
title = {A note on the Bayesian analysis of experiments with correlated multiple responses using a matrixlogarithmic covariance model},
author = {Hamada, Michael S. and Jaramillo, Brandon M. and Chiao, Chih‐Hua},
abstractNote = {In the literature, analysis of multiple responses from experiments with replicates has modeled the covariance matrix directly as linear models of the transformed variances and correlations, i.e., covariance modeling. This article considers models based on the matrix logarithm of the covariance matrix. This socalled logcovariance modeling is illustrated with data from actual experiments and compared with the traditional covariance modeling.},
doi = {10.1002/qre.2540},
journal = {Quality and Reliability Engineering International},
number = 7,
volume = 35,
place = {United States},
year = {2019},
month = {7}
}
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