Browsing by Department "Mathematics and Statistics"
Now showing items 221-240 of 283
Quasi-static poroelastic equations as a symmetric positive system and its numerical approximation
(2015-12-11)
This dissertation is concerned with the equations of linear poroelasticity and numerical simulation in the framework of symmetric positive systems. Physical systems arising in geomechanics, hydrology, soil mechanics, ...
Rainbow Cycle Forbidding Edge Colorings
(2019-07-18)
It is well known that K_n can be edge colored using n-1 colors in order to avoid rainbow cycles; moreover, this is the maximum number of colors possible. We call such an edge coloring a JL-coloring. In previous work it has ...
Rainbow Trees in Edge-Colored Complete Graphs and Block Decompositions of Almost Complete Graphs
(2017-04-26)
This dissertation focuses on two problems, the first involving the existence of many edge-disjoint rainbow spanning trees in edge-colored complete graphs, and the second, creating a balanced sampling plan for a two-dimensional ...
Random and Vector Measures: from "Toy" Measurable Systems to Quantum Probability
(2013-07-10)
Vector measure theory and Bochner integration have been well studied over the past century. This work is an introduction to both theories and explores various examples and
applications in each. The theories and theorems ...
Random Time Change and Some Applications
(2014-04-25)
This thesis is a survey of known results concerning random time change and its applications. It will cover basic probabilistic concepts and then follow with a detailed look at major results in several branches of probability ...
Rank Based Group Variable Selection for Functional Linear Model
(2019-12-09)
We propose a robust rank based variable selection method for a functional linear regression model with multiple explanatory functions and a scalar response. The procedure extends rank based group variable selection to ...
Rank Based Methods for Repeated Measurement Data
(2011-05-16)
This dissertation considers rank based methods for one sample and two sample repeated measurement data. As a specific example, in Chapter 2, this dissertation considers nonparametric tests for selective predation. ...
Rank-Based Estimation for Generalized Additive Models
(2016-07-08)
This thesis focuses on the improvement of generalized additive models (GAMs) using rank estimators. We introduce estimation of the smoothing functions in GAMs via backfitting in a local scoring algorithm using maximization ...
Rank-Based Methods for Single-Index Varying Coefficient Models
(2017-06-27)
The single-index varying coefficient model has received much attention due to its flexibility and interpretability in recent years. This dissertation is mainly concerned with the rank-based estimation and variable selection ...
Rank-Based Regression for Nonlinear and Missing Response Models
(2012-07-09)
This dissertation is mainly concerned with the rank-based estimation of model parameters in complex regression models: a general nonlinear regression model and a semi-parametric regression model with missing responses. For ...
Revisiting the Intersection Problem for Maximum Packings of K_(6n+5) with Triples
(2017-04-16)
In 1989, Gaetano Quattrocchi gave a complete solution of the intersection problem for maximum packings of K_(6n+5) with triples when the leave (a 4--cycle) is the same in each maximum packing. Quattrocchi showed that I[2]=2 ...
Robust Bayesian Methods for Semi-parametric Models
(2020-07-21)
Nonparametric rank-based approaches in many situations provide more flexible modeling speci cations and robustness when the distribution of data diff ers from the assumed distribution. This dissertation is mainly concerned ...
Robust Estimation and Selection for Semi-Varying Coefficient Models
(2022-07-28)
Varying coefficient models have gained popularity in recent years due to their
exibility
in modeling more realistic problems. On the other hand, parametric models provide better
interpretability. Model selection can ...
Robust Group Variable Selection Methods for Multiple Functional Regression Model
(2015-07-29)
With the advancements in science and ever changing technology to collect data, functional data have become common these days, especially in various fields such as neuroscience, chemometrics, e-commerce and computer science. ...
Robust Methods for Functional Data Analysis
(2009-07-06)
Functional data consist of observed functions or curves at a finite subset of an interval. Each functional observation is a realization from a stochastic process. This thesis aims to develop suitable statistical methodologies ...
Robust Methods for Multivariate Functional Data Analysis
(2013-07-16)
In the present work we have proposed a robust multivariate functional principal component analysis (RMFPCA) method, that is efficient in estimation and fast in computation, to achieve dimension reduction of dataset and to ...
Robust Nonparametric Discriminant Analysis Procedures
(2009-05-15)
In this study, a nonparametric discriminant analysis procedure that is less sensitive than traditional procedures to deviations from the usual assumptions is proposed. The procedure uses the projection pursuit methodology ...
Robust Partial Least Squares for Regression and Classification
(2008-08-15)
Partial Least Squares (PLS) is a class of methods for modeling relations between sets of observed variables ...
Robust Simultaneous Inference for Functional Data
(2017-04-20)
Advancements in modern technology have enabled the collection of complex, high- dimensional data sets, such as curves, 2D or 3D images, and other objects living in a functional space, thus boosting the investigation of ...
Robust Statistical Methods for the Functional Logistic Model
(2013-07-10)
Over the last decade or so, a lot of interest has emerged in the field of functional data analysis. This interest spans from a broad spectrum of fields such as brain imaging studies, bio-metrics, genetics, e-commerce and ...