Browsing by Author "Zinn, Joel"
Now showing items 120 of 27

Adaptive Basis Sampling for Smoothing Splines
Zhang, Nan (20150803)Smoothing splines provide flexible nonparametric regression estimators. Penalized likelihood method is adopted when responses are from exponential families and multivariate models are constructed with certain analysis of ... 
Bootstrapping General Empirical Measures
Gine, Evarist; Zinn, Joel (Annals of Probability, 1990) 
Bootstrapping in a high dimensional but very low sample size problem
Song, Juhee (Texas A&M University, 20060816)High Dimension, Low Sample Size (HDLSS) problems have received much attention recently in many areas of science. Analysis of microarray experiments is one such area. Numerous studies are ongoing to investigate the behavior ... 
Central Limit Theorems for Empirical Processes Based on Stochastic Processes
Yang, Yuping (20130813)In this thesis, we study timedependent empirical processes, which extend the classical empirical processes to have a time parameter; for example the empirical process for a sequence of independent stochastic processes {Yi ... 
A CLT for empirical processes involving timedependent data
Kuelbs, James; Kurtz, Thomas; Zinn, Joel (Annals of Probability, 2013) 
Distributed Signal Processing over LargeScale Complex Systems
Li, Di (20170313)Largescale and complex dynamical networks with highdimension states have been emerging in the era of big data, which potentially generate massive data sets. To deal with the massive data sets, one promising method is the ... 
Efficient Estimation in a Regression Model with Missing Responses
Crawford, Scott (20121019)This article examines methods to efficiently estimate the mean response in a linear model with an unknown error distribution under the assumption that the responses are missing at random. We show how the asymptotic variance ... 
Embeddings and factorizations of Banach spaces
Zheng, Bentuo (20090515)One problem, considered important in Banach space theory since at least the 1970’s, asks for intrinsic characterizations of subspaces of a Banach space with an unconditional basis. A more general question is to give necessary ... 
An empirical Bayes approach to variance function estimation
Hwang, LieJu (Texas A&M University. Libraries, 1990)The problem concerns the analysis of assay data when there have been previous similar experiments. Assay data usually fall under the framework of nonlinear regression when the variability about the regression line is ... 
Estimation in spatial time series
Stevens, Gary Richard (Texas A&M University. Libraries, 1986)Several different methods of modeling and analyzing spatial data are discussed. The problems associated with estimation of the parameters of the models are noted and various methods to avoid these problems are presented. ... 
Investigation of a Markov Chain on Ferrers Boards
Linz, William Barham (20160429)This thesis is an investigation of some of the basic combinatorial, algebraic and probabilistic properties of a Markov chain on Ferrers Boards (i.e., a Markov chain whose states are permutations on a given Ferrers Board). ... 
L^p Bernstein Inequalities and Radial Basis Function Approximation
Ward, John P. (20121019)In approximation theory, three classical types of results are direct theorems, Bernstein inequalities, and inverse theorems. In this paper, we include results about radial basis function (RBF) approximation from all three ... 
LASSO Asymptotics For Heavy Tailed Errors
Goldsmith, Aaron Seth (20151214)We consider the asymptotic behavior of the l^1 regularized least squares estimator (LASSO) for the linear regression model Y=X(beta)+xi with training data (X,Y) in R^{nxp}xR^n, true parameter beta in R^p, and observation ... 
Limited Dependent Variable Correlated Random Coefficient Panel Data Models
Liang, Zhongwen (20121019)In this dissertation, I consider linear, binary response correlated random coefficient (CRC) panel data models and a truncated CRC panel data model which are frequently used in economic analysis. I focus on the nonparametric ... 
Mathematical Foundations and Algorithms for Clique Relaxations in Networks
Pattillo, Jeffrey (20120214)This dissertation establishes mathematical foundations for the properties exhibited by generalizations of cliques, as well as algorithms to find such objects in a network. Cliques are a model of an ideal group with roots ... 
New Approaches in Testing Common Assumptions for Regressions with Missing Data
Chown, Justin Andrew (20140730)We consider both nonparametric regression and heteroskedastic nonparametric regression models with multivariate covariates and with responses missing at random. The regression function is estimated using a local polynomial ... 
Nonparametric Inference for High Dimensional Data
Mukhopadhyay, Subhadeep (20130423)Learning from data, especially ‘Big Data’, is becoming increasingly popular under names such as Data Mining, Data Science, Machine Learning, Statistical Learning and High Dimensional Data Analysis. In this dissertation we ... 
Normalization methods in the bootstrap central limit theorem
Sepanski, Steven J. (Texas A&M University. Libraries, 1991) 
Novel Pattern Recognition Approaches to Identification of GeneExpression Pathways in Banana Cultivars
Jiang, Xingde (20160818)Bolstered resubstitution is a simple and fast error estimation method that has been shown to perform better than crossvalidation and comparably with bootstrap in smallsample settings. However, it has been observed that ... 
A Remark on Convergence in Distribution of $U$Statistics
Gine, Evarist; Zinn, Joel (Annals of Probability, 1994)