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This content will become publicly available on October 18, 2017

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

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:
OSTI Identifier:
1331284
Report Number(s):
LA-UR--16-23342
Journal ID: ISSN 0898-2112
Grant/Contract Number:
AC52-06NA25396
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
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States). Center for Integrated Nanotechnologies (CINT)
Sponsoring Org:
Office of the Secretary of Defense; USDOE
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING mathematics