Browsing Theses and Dissertations (MU) by Thesis Department "Statistics (MU)"
Now showing items 2140 of 78

Bayesian smoothing spline models and their application in estimating yield curves
(University of MissouriColumbia, 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 ... 
Bayesian spatial analysis with application to the Missouri Ozark Forest ecosystem project
(University of MissouriColumbia, 2008)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Bayesian hierarchical framework brings more flexibility by accounting for variation from different levels and improves the estimation of parameters as ... 
Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project
(University of MissouriColumbia, 2006)The first part studies the problem of estimating the covariance matrix in a starshaped model with missing data. By introducing a class of priors based on a type of Cholesky decomposition of the precision matrix, we then ... 
Bayesian spatial models for adjusting nonresponse in small area estimation
(University of MissouriColumbia, 2010)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] There are two kinds of nonresponse: item nonresponse and unit nonresponse. Inferences made from respondents about the population of interest will be ... 
Bayesian variable selection in parametric and semiparametric high dimensional survival analysis
(University of MissouriColumbia, 2011)In this dissertation, we propose several Bayesian variable selection schemes for Bayesian parametric and semiparametric survival models for rightcensored survival data. In the rst chapter we introduce a special shrinkage ... 
Design and analysis of a new bounded loglinear regression model
(University of MissouriColumbia, 2013)This dissertation introduces a new regression model in which the response variable is bounded by two unknown parameters. A special case is a bounded alternative to the four parameter logistic model which is also called the ... 
Empirical likelihood approach estimation of structural equation models
(University of MissouriColumbia, 2007)This thesis provides a preliminary investigation of empirical likelihood approach estimation of structural equation models. An auxiliary variable approach built on general estimating equation methods in the EL settings is ... 
Equivalence test of high dimensional microarray data
(University of MissouriColumbia, 2014)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The Booth lab at the University of Missouri has selectivelybred Wistar rats for low (LVR) and high (HVR) voluntary running behavior as a model for ... 
Estimates of school productivity and implications for policy
(University of MissouriColumbia, 2007)School productivity was not perfectly estimated because of the sampling error and the measurement error. The traditional Ordinary Least Square (OLS) leaves the estimation of school productivity questionable. Moreover, ... 
Estimating population size with objective Bayesian methods
(University of MissouriColumbia, 2012)Bayesian inference of discrete parameter, including population size, is sensitive to the choice of priors. In this dissertation I will develop objective priors for several population size parameters appeared in different ... 
Flexible Bayesian Hierarchical Models for DiscreteValued SpatioTemporal Data
(University of MissouriColumbia, 2014) 
The formal definition of reference priors under a general class of divergence
([University of MissouriColumbia], 2014)Bayesian analysis is widely used recently in both theory and application of statistics. The choice of priors plays a key role in any Bayesian analysis. There are two types of priors: subjective priors and objective priors. ... 
Full Bayesian models for paired RNAseq data and Bayesian equivalence test
(University of MissouriColumbia, 2018)In my doctorate research, I have developed Bayesian models to analyze the paired RNAseq data for different types of design. The developed methods are especially of important practice for gene expression analysis using high ... 
Functional data analysis : children's mathematical development
(University of MissouriColumbia, 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. ... 
A hierarchical Bayesian mixture approach for modeling reflectivity fields with application to Nowcasting
(University of MissouriColumbia, 2009)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] We study a hierarchical Bayesian framework for finite mixtures of distributions. We first consider a Dirichlet mixture of normal components and utilize ... 
Hierarchical modeling of nonlinear multivariate spatiotemporal dynamical systems in the presence of uncertainty
(University of MissouriColumbia, 2012)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Dynamic spatiotemporal models are statistical models that specify the joint distribution of a spatiotemporal process as the product of a series of ... 
Hierarchical nonlinear, multivariate, and spatiallydependent timefrequency functional methods
(University of MissouriColumbia, 2013)Notions of time and frequency are important constituents of most scientific inquiries, providing complimentary information. In an era of “big data,” methodology for analyzing functional and/or image data is increasingly ... 
Hierarchical physicalstatistical forecasting in the atmospheric sciences
(University of MissouriColumbia, 2009)[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] A class of hierarchical Bayesian models is introduced for PhysicalStatistical forecasting purposes in the Atmospheric Sciences. The first project ... 
Hierarchical spatiotemporal models for ecological processes
(University of MissouriColumbia, 2006)Ecosystems are composed of phenomena that propagate in time and space. Often, ecological processes underlying such phenomena are studied separably in various subdisciplines, while larger scale, interlinking mechanisms are ... 
Hierarchical spatiotemporal models for environmental processes
(University of MissouriColumbia, 2007)The processes governing environmental systems are often complex, involving different interacting scales of variability in space and time. The complexities and often high dimensionality of such spatiotemporal processes can ...