Browsing Graduate School  Theses and Dissertations (MU) by Thesis Department "Statistics (MU)"
Now showing items 120 of 81

Adaptive optimal design with application to a two drug combination trial based on efficiencytoxicity response
(University of MissouriColumbia, 2009)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The first part of this dissertation develops an adaptive optimal design for dosefinding with combination therapies that accounts for both efficacy and ... 
Adaptive optimal designs for dosefinding studies and an adaptive multivariate CUSUM control chart
(University of MissouriColumbia, 2013)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] There are many areas where optimal designs are applied to, for example, the development of a new drug, where a conventional dose finding study involves ... 
A ballooned betalogistic model
(University of MissouriColumbia, 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. ... 
Bayes factor consistency in linear models when p grows with n
(University of MissouriColumbia, 2009)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation examines consistency of Bayes factors in the model comparison problem for linear models. Common approaches to Bayesian analysis of ... 
Bayesian analysis for detecting differentially expressed genes from RNAseq data
(University of MissouriColumbia, 2014)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation introduces hmmSeq, a modelbased hierarchical Bayesian technique for detecting differentially expressed genes from RNAseq data. Our ... 
Bayesian analysis of capturerecapture model and diagnostic test in clinical trials
(University of MissouriColumbia, 2014)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Capturerecapture models have been widely used to estimate the size of a target wildlife population. There are three major sources of variations that ... 
Bayesian analysis of fMRI data and RNASeq Time Course experiment data
(University of MissouriColumbia, 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 analysis of multivariate stochastic volatility and dynamic models
(University of MissouriColumbia, 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 ... 
Bayesian analysis of spatial and survival models with applications of computation techniques
(University of MissouriColumbia, 2012)This dissertation discusses the methodologies of applying Bayesian hierarchical models to different data with geographical characteristics or with rightcensored failure time. A conditional autoregressive (CAR) prior is ... 
A Bayesian classification framework with label corrections
(University of MissouriColumbia, 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 fMRI data analysis and Bayesian optimal design
(University of MissouriColumbia, 2012)The present dissertation consists of the work done on two projects. As part of the first project, we develop methodology for Bayesian hierarchical multisubject multiscale analysis of functional magnetic resonance imaging ... 
Bayesian hierarchical modeling of colorectal and breast cancer data in Missouri
(University of MissouriColumbia, 2018)Data on cancer in the United States is collected through cancer registries. The Missouri Cancer Registry and Research Center (MCRARC) maintains a statewide cancer surveillance system and participate in research in support ... 
Bayesian hierarchical models for estimating nest survival
(University of MissouriColumbia, 2015)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Nest survival rate is a critical value in avian study to evaluate the landbirds populations. The widely used likelihoodbased logistic regression model ... 
Bayesian hierarchical models for estimating nest survival
(University of MissouriColumbia, 2015)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Nest survival rate is a critical value in avian study to evaluate the landbirds populations. The widely used likelihoodbased logistic regression model ... 
Bayesian hierarchical models for the recognitionmemory experiments
(University of MissouriColumbia, 2008)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Bayesian hierarchical probit models are developed for analyzing the data from the recognitionmemory experiment in Psychology. Both informative priors ... 
Bayesian lasso for random intercept factor model
(University of MissouriColumbia, 2013)Structural Equation Models (SEM) are often used in psychological research. In many studies, determining the number of variables is di fficult because maximum likelihood estimates are empirically underidenti fied when more ... 
Bayesian methods on selected topics
(University of MissouriColumbia, 2012)Bayesian methods are widely adopted nowadays in statistical analysis. It is especially useful for the statistical inference of complex models or hierarchical models, for which the frequentist methods are usually difficult ... 
Bayesian nonlinear methods for survival analysis and structural equation models
([University of MissouriColumbia], 2014)High dimensional data are more common nowadays, because the collection of such data becomes larger and more complex due to the technology advance of the computer science, biology, etc. The analysis of high dimensional data ... 
Bayesian partition model for identifying hypo and hyper methylation
(University of MissouriColumbia, 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 ... 
Bayesian semiparametric spatial and joint spatiotemporal modeling
(University of MissouriColumbia, 2006)Over the past decades a great deal of effort has been expended in the collection and compilation of high quality data on cancer incidence and mortality in the United States. These data have largely been used in the creation ...