Forecast Uncertainty Quantification
Forecast Uncertainty Quantification is a formal methodological framework within predictive analytics that characterizes the inherent stochastic variability and systematic lack of precision in forecasted outcomes by quantifying the range and likelihood of potential deviations between predicted and actual values under uncertain conditions.
493
Publications
29.8K
Citations
1.6K
Authors
664
Institutions
Publications per year
2017–2026
189
Variants
Forecast Uq
493
Economic uncertainty before and during the COVID-19 pandemic
Dave Altig, Scott Baker, Jose Maria Barrero et al. · Journal of Public Economics · 2020 · 993 citations · Full text
Justin Wolfers, Eric Zitzewitz · The Journal of Economic Perspectives · 2004 · 788 citations · Full text
1–5 of 493
1.6K
9
h-index
7
h-index
7
h-index
7
h-index
6
h-index
1–5 of 1.6K
664

NSF National Center for Atmospheric Research
Boulder, United States
13 h-index
34 publications
3.8K citations
University of Reading
Reading, United Kingdom
12 h-index
28 publications
3.3K citations

European Centre for Medium-Range Weather Forecasts
Reading, United Kingdom
11 h-index
24 publications
2.4K citations

Delft University of Technology
Delft, The Netherlands
11 h-index
15 publications
1K citations

National Bureau of Economic Research
Cambridge, United States
11 h-index
14 publications
2.6K citations
Federal Reserve Board of Governors
Washington D.C., United States
10 h-index
13 publications
1.4K citations
University of California San Diego
San Diego, United States
10 h-index
22 publications
1.1K citations

Centre National de la Recherche Scientifique
Paris, France
10 h-index
22 publications
1.8K citations
1–8 of 664
21 publications · 1.8K citations
18
h-index
Repository · 25 publications · 879 citations
16
h-index
17 publications · 1.1K citations
16
h-index
16 publications · 1K citations
14
h-index
13 publications · 860 citations
13
h-index
1–5