Now showing items 1-3 of 3
Topics in objective bayesian methodology and spatio-temporal models
(University of Missouri--Columbia, 2008)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Three distinct but related topics contribute my work in objective Bayesian methodology and spatio-temporal models. This dissertation starts with the study of a class...
Modeling gibbs point processes through basic function decompositions
(University of Missouri--Columbia, 2019)
of Chicago for 2015, where we include as covariate information the American Community Survey 5-year period estimate of median income at the Census tract level....
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 data assimilation setting...