Browsing by Thesis Department "Statistics"
Now showing items 2140 of 53

A hierarchical Bayesian mixture approach for modeling reflectivity fields with application to Nowcasting
(University of MissouriColumbia, 2009)We study a hierarchical Bayesian framework for finite mixtures of distributions. We first consider a Dirichlet mixture of normal components and utilize it to model spatial fields that arise as pixelated images of intensities. ... 
Hierarchical modeling of nonlinear multivariate spatiotemporal dynamical systems in the presence of uncertainty
(University of MissouriColumbia, 2012)Dynamic spatiotemporal models are statistical models that specify the joint distribution of a spatiotemporal process as the product of a series of conditional models whereby the current value of the process is conditioned ... 
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)A class of hierarchical Bayesian models is introduced for PhysicalStatistical forecasting purposes in the Atmospheric Sciences. The first project describes a methodological approach to implement a stochastic trigger ... 
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 ... 
Marginally modeling misaligned regions and handling masked failure causes with imprecision
(University of MissouriColumbia, 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. ... 
A mixed model for variance of successive difference of stationary time series: modeling temporal instability in intensive longitudinal data
(University of MissouriColumbia, 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 ... 
Multiple imputation approaches to regression analysis of intervalcensored failure time data
(University of MissouriColumbia, 2009)This dissertation discusses regression analysis of intervalcensored failure time data, which occur in many fields including demographical, epidemiological, financial, medical, and sociological studies (Sun, 2006). It ... 
Nonparametric analysis of intervalcensored failure time data
(University of MissouriColumbia, 2009)This thesis considers the problem of treatment comparisons when only intervalcensored failure time data are available. This type of data occurs frequently in clinical trials and other followup studies. We study several ... 
The nonparametric analysis of intervalcensored failure time data
(University of MissouriColumbia, 2013)By intervalcensored failure time data, we mean that the failure time of interest is observed to belong to some windows or intervals, instead of being known exactly. One would get an intervalcensored observation for a ... 
Nonparametric and semiparametric methods for intervalcensored failure time data
(University of MissouriColumbia, 2006)Intervalcensored failure time data commonly arise in followup studies such as clinical trials and epidemiology studies. By intervalcensored data, we mean that the failure time of interest is not completely observed. ... 
Objective Bayesian inference for stressstrength models and Bayesian ANOVA
(University of MissouriColumbia, 2012)First of all, for estimating the reliabilities in Weibull stressstrength models, some matching priors are derived based on a modi ed pro le likelihood. Simulation studies show that these matching priors perform well with ... 
Optimal designs for dosefinding in contingent response models
(University of MissouriColumbia, 2004)We study D and coptimal designs for dosefinding 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 ... 
Optimal designs for response functions with a downturn
(University of MissouriColumbia, 2010)In many toxicological assays, interactions between primary and secondary effects may cause a downturn in mean responses at high doses. In this situation, the typical monotonicity assumption is invalid and may be quite ... 
OPTIMAL EXPERIMENTAL DESIGN UNDER A NEW MULTIVARIATE WEIBULL REGRESSION FUNCTION
(University of MissouriColumbia, 2014)Statistics 
Regression analysis of clustered intervalcensored failure time data
(University of MissouriColumbia, 2012)Clustered failure time data occur when the failure times of interest are clustered into small groups, while interval censoring occurs when the event of interest cannot be observed directly and is only known to have occurred ... 
Regression analysis of clustered intervalcensored failure time data with informative cluster size
(University of MissouriColumbia, 2010)Correlated or clustered failure time data often occur in many research fields including epidemiological, geographical, sociological and medical studies. Sometimes such data arise together with interval censoring and the ... 
Semiparametric regression analysis of intervalcensored failure time data
(University of MissouriColumbia, 2014)Statistics 
Semiparametric analysis of multivariate longitudinal data
(University of MissouriColumbia, 2008)Longitudinal studies are conducted widely in fields such as agriculture and life sciences, business and industry, demography and other social sciences, medicine and public health. In longitudinal studies, individuals are ...