Browsing Department of Statistics (MU) by Thesis Advisor "Wikle, Christopher K., 1963-"
Now showing items 1-7 of 7
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Hierarchical modeling of nonlinear multivariate spatio-temporal dynamical systems in the presence of uncertainty
(University of Missouri--Columbia, 2012)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Dynamic spatio-temporal models are statistical models that specify the joint distribution of a spatio-temporal process as the product of a series of ... -
Hierarchical nonlinear, multivariate, and spatially-dependent time-frequency functional methods
(University of Missouri--Columbia, 2013)Notions of time and frequency are important constituents of most scientific inquiries, providing complimentary information. In an era of "big data," methodology for analyzing functional and/or image data is increasingly ... -
Hierarchical physical-statistical forecasting in the atmospheric sciences
(University of Missouri--Columbia, 2009)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] A class of hierarchical Bayesian models is introduced for Physical-Statistical forecasting purposes in the Atmospheric Sciences. The first project ... -
Hierarchical spatio-temporal models for ecological processes
(University of Missouri--Columbia, 2006)Ecosystems are composed of phenomena that propagate in time and space. Often, ecological processes underlying such phenomena are studied separably in various subdisciplines, while larger scale, interlinking mechanisms are ... -
Hierarchical spatio-temporal models for environmental processes
(University of Missouri--Columbia, 2007)The processes governing environmental systems are often complex, involving different interacting scales of variability in space and time. The complexities and often high dimensionality of such spatio-temporal processes can ... -
Spatio-temporal models with time-varying spatial model error for environmental processes
(University of Missouri--Columbia, 2013)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Environmental processes exhibit uncertainty in the spatial and temporal domains. Often, mechanistic forecast models, such as weather forecasting systems, ... -
Statistical-based dynamic machine learning models for nonlinear spatio-temporal processes
(University of Missouri--Columbia, 2018)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] One of the most vital aspects of any spatio-temporal model is characterizing the dynamics of the process. In both a spatio-temporal forecasting and ...