Search
Now showing items 1-3 of 3
Hierarchical nonlinear, multivariate, and spatially-dependent time-frequency functional methods
(University of Missouri--Columbia, 2013)
through carefully chosen basis expansions (empirical orthogonal functions) and feature-extraction stochastic search variable selection (SSVS). Properties of the methodology are examined through an extensive simulation study. Finally, we illustrate...
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 ...
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 ...