Browsing by Author "Zinn, Joel"
Now showing items 1-20 of 27
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Zhang, Nan (2015-08-03)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 ...
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Gine, Evarist; Zinn, Joel (Annals of Probability, 1990)
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Song, Juhee (Texas A&M University, 2006-08-16)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 on-going to investigate the behavior ...
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Yang, Yuping (2013-08-13)In this thesis, we study time-dependent 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 ...
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Kuelbs, James; Kurtz, Thomas; Zinn, Joel (Annals of Probability, 2013)
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Li, Di (2017-03-13)Large-scale and complex dynamical networks with high-dimension 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 ...
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Crawford, Scott (2012-10-19)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 ...
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Zheng, Bentuo (2009-05-15)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 ...
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Hwang, Lie-Ju (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 ...
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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. ...
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Linz, William Barham (2016-04-29)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). ...
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Ward, John P. (2012-10-19)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 ...
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Goldsmith, Aaron Seth (2015-12-14)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 ...
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Liang, Zhongwen (2012-10-19)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 ...
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Pattillo, Jeffrey (2012-02-14)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 ...
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Chown, Justin Andrew (2014-07-30)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 ...
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Mukhopadhyay, Subhadeep (2013-04-23)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 ...
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Sepanski, Steven J. (Texas A&M University. Libraries, 1991)
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Jiang, Xingde (2016-08-18)Bolstered resubstitution is a simple and fast error estimation method that has been shown to perform better than cross-validation and comparably with bootstrap in small-sample settings. However, it has been observed that ...
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Gine, Evarist; Zinn, Joel (Annals of Probability, 1994)