The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $200,000 Project Grant to The University Corporation, a non-profit organization located in Northridge, CA. The grant, funded under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), focuses on developing new statistical modeling and data resampling methods to address challenges posed by incomplete, missing, and fragmented observations in large datasets. Key objectives include: Advancing...
The National Science Foundation awarded a $275,000 Project Grant to the University of Southern California under the Mathematical and Physical Sciences program (CFDA 47.049) from July 1, 2023 to June 30, 2026. The grant funds the development of new exploratory data analysis and inference methods for complex data that lack fundamental vector space properties. The university will create a practical toolkit of theoretically sound, user-friendly tools to enable common data analysis tasks like...
The University of Southern California will receive $200,000 in funding from the National Science Foundation under the Mathematical and Physical Sciences program (CFDA 47.049) to conduct collaborative research on flexible network inference from July 1, 2021 to June 30, 2024. The goal of this three-year project grant award is to advance the scientific understanding of major problems in network analysis through flexible modeling approaches. As part of the work, the University will leverage its...
This $149,989 Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will support research to develop statistical models and inference methods for analyzing random point processes. The research will provide tools for analyzing time series of point process data, with applications in fields such as national security, economics, neuroscience, and geosciences. Key activities include developing parameter estimation procedures,...
This $289,999 National Science Foundation project grant, awarded under the Mathematical and Physical Sciences program (CFDA 47.049), will fund the development of improved statistical methods, algorithms, and theory for estimation and inference with high-dimensional data at Rutgers, The State University from July 2022 through June 2025. Key products include new statistical methods for regularized estimation, de-biased statistical inference including confidence intervals and regions, and empirical...
This $155,372 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will fund research to develop advanced statistical methods for extracting insights from high-dimensional, high-frequency "big data." The University of Illinois, Chicago, as the prime awardee, will focus on four key areas: 1) advancing contiguity theory to enable more robust statistical analysis of noisy, high-frequency data; 2) exploring time-varying...
This Project Grant award, with a total funding amount of $150,000.00, was provided by the National Science Foundation's (NSF) Division of Mathematical Sciences under the CFDA program "Mathematical and Physical Sciences." The award aims to develop scalable subsampling algorithms for statistical inference on large-scale networks across scientific fields, including biological and social sciences. The project will investigate the theoretical properties of these subsampling methods to...
This $169,999 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports collaborative research at the University of California, Davis (UC Davis) to advance innovative nonparametric data analysis techniques. The project aims to conduct comprehensive statistical and computational analyses to push the boundaries of modern nonparametric statistical inference, with potential applications in areas like nonparametric latent...
This $146,738 federal Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences grant program (CFDA 47.049) supports collaborative research on statistical inference methods for multivariate and functional time series data. The primary awardee, The Washington University, will develop a new unified framework using sample splitting and self-normalization techniques to enable robust statistical inference for time...
This Project Grant award of $179,999 from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports comprehensive statistical and computational analyses with the goal of advancing innovative nonparametric data analysis techniques. The research aims to push the boundaries of modern nonparametric statistical inference and develop methodologies applicable to areas such as latent variable models, time series analysis, and sequential nonparametric...