Collaborative Research: Generalized Fiducial Inference in Complex Systems: Causal Inferenc — NSF Award to University of North Caro
Accurate statistical inference is essential for making reliable decisions in various fields, such as forensic science, medicine, economics, and machine learning. This project develops and advances generalized fiducial inference (GFI), an innovative statistical method that quantifies uncertainty without requiring subjec
| Award title | Collaborative Research: Generalized Fiducial Inference in Complex Systems: Causal Inferenc |
|---|---|
| Award ID | 2515303 |
| Awardee | University of North Carolina at Chapel Hill |
| City | CHAPEL HILL |
| State | NC |
| Amount obligated | $125,000 |
| Principal investigator | Jan Hannig |
| Program | STATISTICS |
| Start date | 09/01/2025 |
| Abstract | Accurate statistical inference is essential for making reliable decisions in various fields, such as forensic science, medicine, economics, and machine learning. This project develops and advances generalized fiducial inference (GFI), an innovative statistical method that quantifies uncertainty without requiring subjective assumptions. By addressing complex real-world problems, such as evaluating evidence in criminal cases, understanding causal relationships in economics and health, and improvin |
| Source | NSF Awards |
$799/mo
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