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 variable models, time series analysis, and sequential nonparametric multiple testing. Key focus areas include nonparametric hypothesis testing, nonparametric variational inference, and nonparametric functional regression, leveraging the synergies between Stein's identities and reproducing kernels. This 3-year award, effective July 1, 2024, will enhance the interconnections among statistics, machine learning, and computation, while providing training opportunities for postdoctoral fellows, graduate students, and undergraduates. No subawards are planned under this grant.
Mod # | Description | Reason For Modification | Federal Obligation (Click to sort descending) | Date (Click to sort ascending) |
|---|---|---|---|---|
| Not listed | $170.0k | 6/17/24 |