Lily Wang, Professor, Statistics, received funding from the National Science Foundation for the project: "Statistical Modelling and Inference for Next-Generation Functional Data."
Wang, her students, and collaborators are developing statistical modeling devices and inference tools with modern computational techniques for high-dimensional functional data over complex domains and papers in progress. For each project, the researchers will study the statistical properties of the estimators, statistical inferences governed by the underlying models, and theoretical properties of the inferences. Wang and her collaborators will summarize research findings in research papers and submit them to peer-reviewed journals.
Second, Wang, her students, and collaborators will devote a significant amount of effort to developing methods to analyze massive functional data in brain imaging studies as stated in the grant proposal.
Third, Wang, her students, and collaborators will also develop high-performance statistical software packages for analyzing next-generation functional data studies and integrate research opportunities and findings from the above activities into disciplinary and interdisciplinary statistical education and graduate student training at Mason.
As for the importance of this project, Wang said, "With the rapid growth of modern technology, many large-scale imaging studies have been or are being conducted to collect massive datasets with large volumes of imaging data, thus boosting the investigation of 'next-generation functional data.' This project targets integrating state-of-the-art statistical modeling devices with modern computational techniques to develop a set of flexible and intelligent statistical models for next-generation functional data with formal statistical inference tools. The research project is important because it significantly enhances the availability of data analysis tools and software in a new era of large-scale imaging data."
Wang received $107,317 from NSF for this project. Funding began in October 2021 and will end in late July 2022.
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