Parameter Estimation Design
Parameter Estimation Design is a Bayesian experimental design strategy that specifies the selection of experimental conditions or observations to maximize the precision and accuracy of posterior parameter inference in a statistical model.
57
Publications
2.5K
Citations
170
Authors
106
Institutions
Publications per year
2017–2026
16
Variants
Optimal Experimental Design
Parents
57
1–5 of 57
170
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106
University of Wisconsin–Madison
Madison, United States
3 h-index
4 publications
362 citations
KU Leuven
Leuven, Belgium
2 h-index
6 publications
84 citations

McGill University
Montreal, Canada
2 h-index
2 publications
57 citations

Lawrence Livermore National Laboratory
Livermore, United States
2 h-index
2 publications
786 citations
United States Geological Survey
Reston, United States
2 h-index
3 publications
1.5K citations
University of New Orleans
New Orleans, United States
2 h-index
4 publications
58 citations
University of Newcastle Australia
Newcastle, Australia
2 h-index
2 publications
786 citations
NOAA National Weather Service
Silver Spring, United States
2 h-index
2 publications
786 citations
1–8 of 106
3 publications · 78 citations
3
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3 publications · 811 citations
3
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2 publications · 60 citations
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2 publications · 55 citations
2
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2 publications · 183 citations
2
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1–5