In contrast with traditional approaches, the methods do not assume any restrictive form, and are flexible enough to detect fine structures. This project covers a wide array of statistics methodological developments and foundational research. The new developments enhance the availability of statistical tools, and can lead to significant improvements on existing methods for extracting information from noisy data. Specific objectives are develop new statistical methodologies and investigate their foundational properties for flexible statistical modeling in processing high-dimensional data, nonparametric confidence intervals, mode detection and signal processing.
Many scientific disciplines depend in some way on extracting structural information from noisy data.
Fields ranging from processing noisy images and evaluating business marketing, to analyzing survival data and forecasting economic climates, which are universes apart in their . . . More on THIS Work .