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 Project Grant award of $194,675 from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research to develop new econometric and statistical methods that allow researchers to draw valid conclusions from complex data in a variety of social, behavioral, and medical science settings. The key products and services to be delivered include: Developing a generally applicable reparameterization procedure for informative...
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...
This $500,000 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) will support research to develop new statistical estimation methods for complex randomized experiments. The award will fund the development of a general framework and theory to enable the estimation of causal effects in randomized experiments with interference, spillover effects, and network structures. The research, to be conducted at Columbia...
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...
This National Science Foundation (NSF) Division of Mathematical Sciences Project Grant, awarded to Carnegie Mellon University, provides $240,000 in funding from September 1, 2023 to August 31, 2026. The grant supports research to advance statistical predictive inference methods, addressing challenges in areas like cross-validation, high-dimensional statistical comparisons, and conformal prediction. The project aims to develop novel techniques with strong mathematical justifications that can...
This award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) provides $160,000.00 to Carnegie Mellon University to develop a new game-theoretic approach to statistical inference. The key products and services to be delivered include: Developing a fundamental theory and methodology for nonparametric, game-theoretic statistical inference, including hypothesis testing, confidence intervals/sequences, and change point detection. This work aims to create more...
This National Science Foundation (NSF) Directorate for Mathematical and Physical Sciences (CFDA 47.049) Project Grant of $229,710 awarded to the University of North Carolina at Charlotte will develop novel semiparametric statistical models and algorithms to enable more effective analysis of censored data, with applications in personalized medicine. The project aims to extend existing transformation models in survival analysis to better handle challenging data structures. Additionally, it will...
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 $200,000 project grant was awarded by the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program to the University of Delaware. The grant will support the development of new nonparametric learning methods for high-dimensional survival data analysis, with applications in causal inference and sequential decision-making problems. The research aims to advance the state-of-the-art in areas like medical risk factor discovery, personalized treatment...