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Bayesian spatial models for adjusting nonresponse in small area estimation
(University of Missouri--Columbia, 2010)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] There are two kinds of nonresponse: item nonresponse and unit nonresponse. Inferences made from respondents about the population of interest will be ...
Regression analysis of clustered interval-censored failure time data with informative cluster size
(University of Missouri--Columbia, 2010)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Correlated or clustered failure time data often occur in many research fields including epidemiological, geographical, sociological and medical studies. ...
Bayesian analysis of capture-recapture model and diagnostic test in clinical trials
(University of Missouri--Columbia, 2014)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Capture-recapture models have been widely used to estimate the size of a target wildlife population. There are three major sources of variations that ...
A ballooned beta-logistic model
(University of Missouri--Columbia, 2015)
The beta distribution is a simple and flexible model in which responses are naturally confined to the finite interval (0,1). Its parameters can be related to covariates such as dose and gender through a regression model. ...
Bayesian analysis for detecting differentially expressed genes from RNA-seq data
(University of Missouri--Columbia, 2014)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation introduces hmmSeq, a model-based hierarchical Bayesian technique for detecting differentially expressed genes from RNA-seq data. Our ...
Bayesian smoothing spline models and their application in estimating yield curves
(University of Missouri--Columbia, 2015)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The term structure of interest rates, also called the yield curve, is the series of interest rates ordered by term to maturity at a given time. The ...
Marginally modeling misaligned regions and handling masked failure causes with imprecision
(University of Missouri--Columbia, 2012)
For many datasets, multiple variables measured on (possibly differing) areal units are available. We wish to simultaneously model both 1) the spatial relations within each variable, and 2) the relations between variables. ...
Bayesian analysis of spatial and survival models with applications of computation techniques
(University of Missouri--Columbia, 2012)
This dissertation discusses the methodologies of applying Bayesian hierarchical models to different data with geographical characteristics or with right-censored failure time. A conditional autoregressive (CAR) prior is ...
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 ...
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 ...
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. ...
Full Bayesian models for paired RNA-seq data and Bayesian equivalence test
(University of Missouri--Columbia, 2018)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] "In my doctorate research, I have developed Bayesian models to analyze the paired RNAseq data for different types of design. The developed methods are ...
Semiparametric methods for regression analysis of panel count data and mixed panel count data
(University of Missouri--Columbia, 2017)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Recurrent event data and panel count data are two common types of data that have been studied extensively in event history studies in literature. By ...
A Bayesian classification framework with label corrections
(University of Missouri--Columbia, 2014)
The use of unlabeled data is very important for regression and classification analysis in many cases. However, the data may have an extra layer of complexity with some wrongly labelled data points. The traditional ...
Bayesian analysis of fMRI data and RNA-Seq time course experiment data
(University of Missouri--Columbia, 2015)
The present dissertation contains two parts. In the first part, we develop a new Bayesian analysis of functional MRI data. We propose a novel triple gamma Hemodynamic Response Function (HRF) including the component to ...
Bayesian partition model for identifying hypo- and hyper- methylation
(University of Missouri--Columbia, 2017)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation introduces MethyBayes, a full Bayesian partition model for identifying hypo- and hypermethylated loci. The main interest of study on ...
Semiparametric analysis of failure time data with complex structures /
(University of Missouri--Columbia, 2016)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Failure time data arise in many fields including biomedical studies and industrial life testing. Right-censored failure time data are often observed ...
Regression analysis of interval-censored failure time data with non proportional hazards models
(University of Missouri--Columbia, 2018)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Interval-censored failure time data arises when the failure time of interest is known only to lie within an interval or window instead of being observed ...