skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Discussion of “Bayesian design of experiments for industrial and scientific applications via gaussian processes”

Abstract

First, we would like to commend Dr. Woods on his thought-provoking paper and insightful presentation at the 4th Annual Stu Hunter conference. We think that the material presented highlights some important needs in the area of design of experiments for generalized linear models (GLMs). In addition, we agree with Dr. Woods that design of experiements of GLMs does implicitly require expert judgement about model parameters, and hence using a Bayesian approach to capture this knowledge is a natural strategy to summarize what is known with the opportunity to incorporate associated uncertainty about that information.

Authors:
 [1];  [1]
  1. 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.:
USDOD; USDOE
OSTI Identifier:
1331284
Report Number(s):
LA-UR-16-23342
Journal ID: ISSN 0898-2112
Grant/Contract Number:  
AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
Quality Engineering
Additional Journal Information:
Journal Name: Quality Engineering; Journal ID: ISSN 0898-2112
Publisher:
American Society for Quality Control
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Mathematics

Citation Formats

Anderson-Cook, Christine M., and Burke, Sarah E. Discussion of “Bayesian design of experiments for industrial and scientific applications via gaussian processes”. United States: N. p., 2016. Web. doi:10.1080/08982112.2016.1246049.
Anderson-Cook, Christine M., & Burke, Sarah E. Discussion of “Bayesian design of experiments for industrial and scientific applications via gaussian processes”. United States. doi:10.1080/08982112.2016.1246049.
Anderson-Cook, Christine M., and Burke, Sarah E. Tue . "Discussion of “Bayesian design of experiments for industrial and scientific applications via gaussian processes”". United States. doi:10.1080/08982112.2016.1246049. https://www.osti.gov/servlets/purl/1331284.
@article{osti_1331284,
title = {Discussion of “Bayesian design of experiments for industrial and scientific applications via gaussian processes”},
author = {Anderson-Cook, Christine M. and Burke, Sarah E.},
abstractNote = {First, we would like to commend Dr. Woods on his thought-provoking paper and insightful presentation at the 4th Annual Stu Hunter conference. We think that the material presented highlights some important needs in the area of design of experiments for generalized linear models (GLMs). In addition, we agree with Dr. Woods that design of experiements of GLMs does implicitly require expert judgement about model parameters, and hence using a Bayesian approach to capture this knowledge is a natural strategy to summarize what is known with the opportunity to incorporate associated uncertainty about that information.},
doi = {10.1080/08982112.2016.1246049},
journal = {Quality Engineering},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {10}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Save / Share: