Search
Now showing items 1-20 of 100
Hierarchical spatio-temporal models for environmental processes
(University of Missouri--Columbia, 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 spatio-temporal processes can ...
Hierarchical spatio-temporal models for ecological processes
(University of Missouri--Columbia, 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 ...
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 ...
Topics in objective bayesian methodology and spatio-temporal models
(University of Missouri--Columbia, 2008)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Three distinct but related topics contribute my work in objective Bayesian methodology and spatio-temporal models. This dissertation starts with the ...
Bayesian spatial analysis with application to the Missouri Ozark Forest ecosystem project
(University of Missouri--Columbia, 2008)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Bayesian hierarchical framework brings more flexibility by accounting for variation from different levels and improves the estimation of parameters ...
Spatially adaptive priors for regression and spatial modeling
(University of Missouri--Columbia, 2008)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The smoothing splines and penalized regression splines (P-splines) are popular nonparametric regression methods for curve fitting problems, and the ...
Semiparametric analysis of multivariate longitudinal data
(University of Missouri--Columbia, 2008)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Longitudinal studies are conducted widely in fields such as agriculture and life sciences, business and industry, demography and other social sciences, ...
Bayesian hierarchical models for the recognition-memory experiments
(University of Missouri--Columbia, 2008)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Bayesian hierarchical probit models are developed for analyzing the data from the recognition-memory experiment in Psychology. Both informative priors ...
Statistical analysis of failure time data with missing information
(University of Missouri--Columbia, 2009)
Failure time data arise in many fields and can involve different types of censoring structures and missing information. We consider three cases: right-censored data with missing censoring indicators, clustered current ...
A hierarchical Bayesian mixture approach for modeling reflectivity fields with application to Nowcasting
(University of Missouri--Columbia, 2009)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] We study a hierarchical Bayesian framework for finite mixtures of distributions. We first consider a Dirichlet mixture of normal components and utilize ...
Bayesian smoothing spline analysis of variance models
(University of Missouri--Columbia, 2009)
Based on the pioneering work by Wahba (1990) in smoothing splines for nonparametric regression, Gu (2002) decomposed the regression function based on a tensor sum decomposition of inner product spaces into orthogonal ...
Nonparametric analysis of interval-censored failure time data
(University of Missouri--Columbia, 2009)
This thesis considers the problem of treatment comparisons when only interval-censored failure time data are available. This type of data occurs frequently in clinical trials and other follow-up studies. We study several ...
A mixed model for variance of successive difference of stationary time series : modeling temporal instability in intensive longitudinal data
(University of Missouri--Columbia, 2008)
Temporal instability of a stochastic process has been of interest in many areas of behavioral and social science. Recent development in data collection techniques in behavioral and health sciences, such as Ecological ...
Optimal designs for response functions with a downturn
(University of Missouri--Columbia, 2010)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] In many toxicological assays, interactions between primary and secondary effects may cause a downturn in mean responses at high doses. In this situation, ...
Statistical analysis for survival data with missing information
(University of Missouri--Columbia, 2009)
As a branch of statistics, survival analysis, which is often referred to as "reliability theory" in engineering, has a long history. While in practical problems, some information might be missing. This dissertation discusses ...
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 methods on selected topics
(University of Missouri--Columbia, 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 ...
Semiparametric transformation models for panel count data
(University of Missouri--Columbia, 2011)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Panel count data arise in event history studies. It may not be feasible to monitor subjects continuously and recurrent events can be observed only at ...
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. ...