Collaborative Research: NSF-SNSF: Tail-robust Analysis of High-dimensional Nonstationary T — NSF Award to University of Georgia Re
High-dimensional time series data arise in many fields such as economics, epidemiology, neuroscience, and social science, where large numbers of measurements are collected over time. These data often exhibit complex patterns, including shifts in behavior and extreme values that violate classical statistical assumptions
| Award title | Collaborative Research: NSF-SNSF: Tail-robust Analysis of High-dimensional Nonstationary T |
|---|---|
| Award ID | 2514399 |
| Awardee | University of Georgia Research Foundation Inc |
| City | ATHENS |
| State | GA |
| Amount obligated | $175,000 |
| Principal investigator | Yuan Ke |
| Program | STATISTICS, GVF - Global Venture Fund |
| Start date | 09/01/2025 |
| Abstract | High-dimensional time series data arise in many fields such as economics, epidemiology, neuroscience, and social science, where large numbers of measurements are collected over time. These data often exhibit complex patterns, including shifts in behavior and extreme values that violate classical statistical assumptions. This project addresses fundamental challenges in analyzing such time series, especially when they are not stationary and prone to abrupt structural changes. The research in this |
| Source | NSF Awards |
$799/mo
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