The National Science Foundation (NSF) Division of Mathematical Sciences awarded a 3-year, $150,000 Project Grant to The Regents of the University of Colorado (University of Colorado) to develop new statistical methods for analyzing extreme weather events such as heatwaves, droughts, and intense precipitation. The research, conducted under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), aims to better understand the spatiotemporal distributions and trends of these extreme...
This $299,965 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences will allow Colorado State University (CSU) to develop and validate a new statistical model and analytical methods for assessing extremal dependence in high-dimensional data. This work aims to improve quantification of joint risks in applications such as finance, insurance, and climate science. The project will include training a graduate student in extreme value analysis techniques...
The National Science Foundation awarded a $441,331 project grant to the University of Texas at Austin under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports research across three topics in stochastic analysis from June 2023 through May 2026. The university will examine Kyle models to study information exchange in financial markets, use backward stochastic differential equations to analyze strategic behavior, and investigate dynamics of fluctuations in financial...
This $150,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports the development of innovative statistical and mathematical methods for time series data analysis. The key objectives of this 2-year project are: a) Developing a variable selection method to identify significant exogenous covariates in autoregressive conditional heteroscedasticity (ARCH) models. b) Designing a novel nonparametric hypothesis test to...
William Marsh Rice University was awarded a $149,994 project grant from the National Science Foundation Division of Mathematical Sciences on August 15, 2021 to complete work by July 31, 2024. The grant falls under the Mathematical and Physical Sciences program (CFDA 47.049), which aims to promote progress in these fields and strengthen the nation's scientific enterprise through increasing knowledge and enhancing understanding of major problems. Specifically, Rice University will conduct...
This $220,000 National Science Foundation project grant supports the development of new statistical inference methodologies for multivariate and functional time series analysis at Texas A&M University from July 2022 through June 2025. The award is funded through the NSF's Mathematical and Physical Sciences program (CFDA 47.049), which supports advancing scientific knowledge and understanding in these fields. Specifically, the university researchers will create a unified framework...
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 (NSF) awarded a $175,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to Arizona State University to develop a geostatistical framework for modeling spatiotemporal extremes, such as heat waves, drought, and intense precipitation. The research aims to better understand the distributions of extreme weather events and develop statistical tools to model the associated spatial and temporal trends and uncertainties. The project will...
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 National Science Foundation (NSF) Project Grant award, under the Mathematical and Physical Sciences (CFDA 47.049) program, will support research on stochastic methods and isoperimetric inequalities at Texas A&M University. The $238,406 award, active from July 2024 to June 2027, will develop techniques to bridge fundamental conjectures in Brunn-Minkowski theory and dual Brunn-Minkowski theory, with a focus on intersection bodies and higher-dimensional generalizations. The research aims...
The National Science Foundation (NSF) awarded a $250,000 Project Grant to William Marsh Rice University in Houston, TX to conduct research on the applications of stochastic analysis to statistical inference for stationary and non-stationary Gaussian processes. This award, under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), aims to provide scientists with demonstrably correct tools for analyzing correlations between time series data, such as global mean temperatures and Atlantic hurricane activity. The research will quantify how correlation coefficients can incorrectly indicate relationships between accumulative time series, a phenomenon known as "Yule's nonsense correlation." The project will also offer research training opportunities for graduate students. This award reflects NSF's mission to advance scientific knowledge and support the nation's scientific enterprise.