Information Function Optimization is a methodological framework within measurement precision that systematically enhances the efficacy of information functions by refining their parameters and structure to maximize reliability and minimize uncertainty in data interpretation.
7
Publications
344
Citations
8
Authors
7
Institutions
Publications per year
2017–2026
1
Parents
Publications
7
1–5 of 7
Authors
8
- EH
1
h-index
- AW
1
h-index
- JC
1
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- JM
1
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- JF
1
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1–5 of 8
Institutions
7
Educational Testing Service
Princeton, United States
1 h-index
1 publications
25 citations
Edwards (United Kingdom)
Crawley, United Kingdom
1 h-index
1 publications
32 citations
New Mexico State University
Las Cruces, United States
1 h-index
1 publications
40 citations
Institute For Defense Analyses
Alexandria, United States
1 h-index
1 publications
19 citations
Pennsylvania State University
State College, United States
1 h-index
2 publications
382 citations
TU Wien
Vienna, Austria
1 h-index
2 publications
50 citations
University of Leicester
Leicester, United Kingdom
1 h-index
1 publications
32 citations
University of Georgia
Athens, United States
1 publications
12 citations
1–8 of 7
Venues
- Journal of Manufacturing Systems
1 publications · 40 citations
1
h-index
- Theory and Decision
1 publications · 32 citations
1
h-index
- ETS Research Bulletin Series
1 publications · 25 citations
1
h-index
- Operations Research
1 publications · 19 citations
1
h-index
- The Journal of Chemical Physics
1 publications · 191 citations
1
h-index
1–5