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Bayesian analysis of multivariate stochastic volatility and dynamic models
(University of Missouri--Columbia, 2006)
We consider a multivariate regression model with time varying volatilities in the error term. The time varying volatility for each component of the error is of unknown nature, may be deterministic or stochastic. We propose ...
Statistical analysis of multivariate interval-censored failure time data
(University of Missouri--Columbia, 2006)
Interval-censored failure time data commonly arise in clinical trials and medical studies. In such studies, the failure time of interest is often not exactly observed, but known to fall within some interval. For multivariate ...
Optimal designs for dose-finding in contingent response models
(University of Missouri--Columbia, 2004)
We study D- and c-optimal designs for dose-finding with opposing failure functions. In particular, we study the contingent response models of Li, Durham and Flournoy (1995). In the contingent response model, there are two ...
Nonparametric and semiparametric methods for interval-censored failure time data
(University of Missouri--Columbia, 2006)
Interval-censored failure time data commonly arise in follow-up studies such as clinical trials and epidemiology studies. By interval-censored data, we mean that the failure time of interest is not completely observed. ...
Modeling gibbs point processes through basic function decompositions
(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 ...
Semiparametric analysis of complex longitudinal data
(University of Missouri--Columbia, 2020)
Event history data consist of the longitudinal records of event occurrence times. Recurrent event data and panel count data are two common types of event history data that occur in many areas, such as medical studies and ...
Variable selection for interval-censored and functional survival data
(University of Missouri--Columbia, 2022)
Interval-censored data are a type of failure time data that is only known to belong to a time interval but cannot be observed precisely. Note that interval-censoring is often encountered in medical or health studies with ...
Variable selection and causal treatment effect estimation based on interval-censored failure time data
(University of Missouri--Columbia, 2022)
Variable selection has been discussed under many contexts and especially a great deal of literature has been established in the failure time context with constant coefficients. However, the time-varying effect sometimes ...
A Bayesian approach to data-driven discovery of nonlinear dynamic equations
(University of Missouri--Columbia, 2022)
Dynamic equations parameterized by differential equations are used to represent a variety of real-world processes. The equations used to describe these processes are generally derived based on physical principles and a ...
Modeling state duration and emission dependence in hidden Markov and hidden semi-Markov models
(University of Missouri--Columbia, 2022)
Hidden Markov models (HMM) are composed of a latent state sequence and an observation sequence conditionally independent on the states, which follows an emission distribution. Hidden semi-Markov models (HSMM) extend the ...
Data combining using mixtures of g-priors with application on county-level female breast cancer prevalence
(University of Missouri--Columbia, 2022)
As more and more data are available, data synthesis has become an indispensable task for researchers. From a Bayesian perspective, this dissertation includes three related projects and aims at quantifying the benefits of ...
Functional data analysis : children's mathematical development
(University of Missouri--Columbia, 2016)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Bailey et al. (2014) suggested that children's mathematical development is related more to trait characteristics than to prior mathematical development. ...
Decision theory and sampling algorithms for spatial and spatio-temporal point processes
(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 ...
Variable selection for interval-censored failure time data
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Variable selection is a commonly asked question and various traditional variable selection methods have been developed, including forward, backward and ...
Bayesian non-parametric methods for benefit-risk assessment and massive multiple-domain data
(University of Missouri--Columbia, 2019)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The development of systematic and structured approaches to assess benefit-risk of medical products is a major challenge for regulatory decision makers. ...
Point processes on the complex plane with applications
(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. ...
Alternative learning strategies for spatio-temporal processes of complex animal behavior
(University of Missouri--Columbia, 2020)
The estimation of spatio-temporal dynamics of animal behavior processes is complicated by nonlinear interactions. Alternative learning methods such as machine learning, deep learning, and reinforcement learning have proven ...
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 ...
Statistical analysis of multivariate interval-censored failure time data
(University of Missouri--Columbia, 2007)
A voluminous literature on right-censored failure time data has been developed in the past 30 years. Due to advances in biomedical research, interval censoring has become increasingly common in medical follow-up studies. ...
Semiparametric analysis of panel count data
(University of Missouri--Columbia, 2007)
Panel count data often arise in long term studies that concern occurrence rates of certain recurrent events. In such studies, each subject is observed only at finite discrete time points instead of continuously, and only ...