Discussion of “Bayesian design of experiments for industrial and scientific applications via gaussian processes”
Journal Article
·
· Quality Engineering
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
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.
- Research Organization:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOD; USDOE
- Grant/Contract Number:
- AC52-06NA25396
- OSTI ID:
- 1331284
- Report Number(s):
- LA-UR-16-23342
- Journal Information:
- Quality Engineering, Journal Name: Quality Engineering; ISSN 0898-2112
- Publisher:
- American Society for Quality ControlCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Cited by: 1 work
Citation information provided by
Web of Science
Web of Science
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Bias reduction of maximum likelihood estimates
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