• Bayesian model averaging for mathematics achievement growth rate trends 

    Kim, Minsun (University of Missouri--Columbia, 2022)
    In this study, we investigated the use of Bayesian model averaging (BMA) for latent growth curve models. We used the Trends in International Mathematics and Science Study (TIMSS) to predict growth rates in 8th-grade students' ...
  • Decision theory and sampling algorithms for spatial and spatio-temporal point processes 

    Chen, Jiaxun (University of Missouri--Columbia, 2019)
    In this work, we first present a flexible hierarchical Bayesian model and develop a comprehensive Bayesian decision theoretic framework for point process theory. Then, we provide a comparative study of the approximate ...
  • Dynamic spatial-temporal point process models via conditioning 

    Okenye, Justin Obwoge (University of Missouri--Columbia, 2021)
    We propose and investigate dynamic spatial-temporal point process models for independent and interacting events. The models for independent events are dynamic spatial-temporal Poisson point process (DSTPPP) model that ...
  • Modeling gibbs point processes through basic function decompositions 

    Hassett, Christopher (University of Missouri--Columbia, 2019)
    [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] We consider non-homogeneous pairwise interaction point process models, where the global and local effect functions are modeled using basis function ...
  • Point processes on the complex plane with applications 

    Wu, Weichao (University of Missouri--Columbia, 2019)
    [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] A point process is a random collection of points from a certain space, and point process models are widely used in areas dealing with spatial data. ...