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Filtering by: Subject Bayesian statistical decision theory Remove constraint Subject: Bayesian statistical decision theory Advisor Gitelman, Alix I. Remove constraint Advisor: Gitelman, Alix I.

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  • Spatial graphical models with discrete and continuous components

    Creator:
    Che, Xuan
    Abstract:
    Graphical models use Markov properties to establish associations among dependent variables. To estimate spatial correlation and other parameters in graphical models, the conditional independences and joint probability distribution of the graph need to be specified. We can rely on Gaussian multivariate models to derive the joint distribution when all the...
    Resource Type:
    Dissertation
    Full Text:
    incorporate some kind of spatial statistical models in their toolbox. Associations between variables and

  • Extensions to Gaussian copula models

    Creator:
    Fang, Yan
    Abstract:
    A copula is the representation of a multivariate distribution. Copulas are used to model multivariate data in many fields. Recent developments include copula models for spatial data and for discrete marginals. We will present a new methodological approach for modeling discrete spatial processes and for predicting the process at unobserved...
    Resource Type:
    Dissertation
    Full Text:
    . We employ Bayesian methodology for both estimation and prediction. Comparisons between the new