This federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program provides $175,000 to the University of Georgia Research Foundation, Inc. (UGA Research Foundation) to initiate a new paradigm for statistical inference of high-dimensional time series data.
The project aims to develop a novel approach using self-normalization techniques to quantify the accumulative uncertainty of high-dimensional time series, and apply this methodology to various statistical inference problems. This research is expected to lead to transformative tools for scientific discovery and analysis of complex, high-dimensional temporal datasets across domains such as economics, neuroscience, finance, telecommunications, and climate science. The project results will also be integrated into undergraduate and graduate education to equip students with advanced statistical methods for analyzing high-dimensional time series. The award period is from August 1, 2024 to July 31, 2027.
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