This Project Grant award from the National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) will support the development of new statistical tools and algorithms to effectively model and analyze dependent data. Cornell University will receive $226,874 to advance this research over a 13-month period from July 2024 to July 2025.
The grant aims to develop innovative approaches for capturing a broad range of data dependencies, providing computational scalability for large datasets, and leveraging dependence structures to enable more adaptive and localized estimation, uncertainty quantification, and imputation of missing data. The research will focus on applications in areas such as local elections and redistricting, inflation modeling and forecasting, spatial pattern extraction, and environmental/exposure data analysis. The project will also provide training and mentoring for students, create publicly available software and visualization tools, and showcase the use of government data sources.