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Selected Problems Of Inference On Branching Processes And Poisson Shock Model, Satrajit Roychoudhury

Dissertations

This dissertation explores the development of statistical methodology for some problems of branching processes and poisson shock model.

Branching process methods have become extremely popular in recent days. This dissertation mainly explores two fundamental inference problems of Galton-Watson processes. The first problem is concerned with statistical inference regarding the nature of the process. Two methodologies have been developed to develop a statistical test for the null hypothesis that the process is supercritical versus an alternative hypothesis that the process is non-supercritical. Another problem we investigate involves the estimation of the 'age' of a Galton-Watson Process. Three different methods are discussed …

The Effect Of Using A Video-Case Curriculum To Promote Preservice Teachers’ Development Of A Reflective Stance Towards Mathematics Teaching, Shari L. Stockero

Dissertations

This study investigates the effects of using a coherent video-case curriculum in a university methods course. In particular, three issues are addressed: (1) howthe use of a video-case curriculum affects the reflective stance of preservice teachers; (2) the extent to which a reflective stance developed while reflecting on other teachers' practice transfers to reflecting on one's own practice; and (3) how preservice teachers' reflective stance that is developed via sustained and focused reflection using a video-case curriculum compares to the reflective stance of peers who engaged in less sustained and focused reflection. Althoughvideo cases are increasingly being used in teacher …

Markov Chain Monte Carlo Methods For Regression Splines With A Penalized Acceptance Ratio, David Keith Stamps

Dissertations

An increasingly popular method for fitting complex models, particularly with a hierchical structure involvese the use of Markov Chain Monte Carlo simulation. Within a Bayesian framework, two major strategies are Gibbs sampling and Metropolis-Hastings methods. Recent research in the area of MCMC methods has witnessed the emergence of modeling efforts which permit the movement of the chain across models of varying dimensions. When properly constructed, such Markov chains converge to the joint posterior distribution of the parameters to be estimated, making Bayesian averaging an attractive option after convergence has occurred. With this transdimensional methodology, the Bayesian averaging process takes place …

Image Segmentation By Energy And Related Functional Minimization Methods, Eric Hudson Mason

Dissertations

Effective and efficient methods for partitioning a digital image into image segments, called ¿image segmentation,¿ have a wide range of applications that include pattern recognition, classification, editing, rendering, and compressed data for image search. In general, image segments are described by their geometry and similarity measures that identify them. For example, the well-known optimization model proposed and studied in depth by David Mumford and Jayant Shah is based on an L₂ total energy functional that consists of three terms that govern the geometry of the image segments, the image fidelity (or closeness to the observed image), and the prior …

Detectable Coloring Of Graphs, Henry E. Escuadro

Dissertations

A basic problem in graph theory is to distinguish the vertices of a connected graph from one another in some manner. In this study, we investigate the problemof coloring the edges of a graph in a manner that distinguishes the vertices of the graph. The method we use combines many of the features of previously introduced methods.

Let G be a connected graph of order n ≥ 3 and let c : E (G ) [arrow right] {1,2,...,k } be a coloring of the edges of G (where adjacent edges may be colored the same). For each vertex …

Linear And Log-Linear Models Based On Generalized Inverse Sampling Scheme, Soumi Lahiri

Dissertations

This dissertation explores the development of novel statistical techniques and the applications in modeling rare events using generalized inverse sampling scheme. The Poisson model can be used for independent frequency count data. Also negative binomial and negative multinomial (NMn) models are applicable when there is only one rare category in the population. Here, a new model, based on generalized inverse sampling scheme, is introduced to study several rare events simultaneouly. The generalized inverse sampling scheme is used to study several rare categories of a population. Samples are drawn until a predetermined number of the total of the rare events occur. …

Mathematical Problems Arising In Interfacial Electrohydrodynamics, Dmitri Tseluiko

Dissertations

In this work we consider the nonlinear stability of thin films in the presence of electric fields. We study a perfectly conducting thin film flow down an inclined plane in the presence of an electric field which is uniform in its undisturbed state, and normal to the plate at infinity. In addition, the effect of normal electric fields on films lying above, or hanging from, horizontal substrates is considered. Systematic asymptotic expansions are used to derive fully nonlinear long wave model equations for the scaled interface motion and corresponding flow fields. For the case of an inclined plane, higher order …

Nilpotent Orbits On Infinitesimal Symmetric Spaces, Joseph A. Fox

Dissertations

Let G be a reductive linear algebraic group defined over an algebraically closed field k whose characteristic is good for G. Let [straight theta] be an involution defined on G, and let K be the subgroup of G consisting of elements fixed by [straight theta]. The differential of [straight theta], also denoted [straight theta], is an involution of the Lie algebra [Special characters omitted.] = Lie (G ), and it decomposes [Special characters omitted.] into +1- and -1-eigenspaces, [Special characters omitted.] and [Special characters omitted.] , respectively. The space [Special characters omitted.] identifies with the tangent space at the …

Testing Procedures For Group Sequential Clinical Trials With Multiple Survival Endpoints, Rebecca C. Scherzer

Dissertations

This research gives methods for sequential monitoring of survival data in clinical trials with multiple endpoints. We illustrate the use of marginal proportional hazards models and other survival models with various group sequential methods to test multiple survival endpoints at K interim analyses. To adjust for multiplicity at each interim analysis, we consider and extend methods developed by Tang and Geller (1999), Follmann, et al. (1994), and others. These methods are motivated, compared, and evaluated using survival data from a clinical study and using simulation studies.