Research Summaries

Back Estimation and Uncertainty Quantification of Stochastic Systems

Fiscal Year 2012
Division Graduate School of Operational & Information Sciences
Department Operations Research
Investigator(s) Royset, Johannes O.
Sponsor Army Research Office (Army)
Summary We will carry out a fundamental study of statistical estimation and function approximation and the use of such estimates in uncertainty quantification, rare-event prediction, and information fusion for a broad range of stochastic systems. We propose to develop a flexible framework for estimation of density functions, regression curves, and other quantities that systematically incorporates hard information derived from physics-based sensors, field test data, and computer simulations as well as soft information from human sources and experiences. The project focuses on two main areas: (i) We will consider complex systems subject to random input parameters and will develop epi-spline-based procedures for constructing functional models of the system as well as for estimating probability density functions, moments, quantiles, and rare events of the resulting random system performance. (ii) In the context of target detection, tracking and situational awareness, we will construct epi-spline-based procedures for information fusion of hard data from physics-based sensors with soft contextual information and predictions from human sources pertaining to past, current, and future time periods.
Keywords
Publications Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal