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You searched for +publisher:"Texas A&M University" +contributor:("Zinn, Joel"). Showing records 1 – 18 of 18 total matches.

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Texas A&M University

1. Pattillo, Jeffrey. Mathematical Foundations and Algorithms for Clique Relaxations in Networks.

Degree: PhD, Mathematics, 2012, Texas A&M University

 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… (more)

Subjects/Keywords: clique relaxations; graph theory; optimization; networks; algorithms; complexity

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APA (6th Edition):

Pattillo, J. (2012). Mathematical Foundations and Algorithms for Clique Relaxations in Networks. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10540

Chicago Manual of Style (16th Edition):

Pattillo, Jeffrey. “Mathematical Foundations and Algorithms for Clique Relaxations in Networks.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10540.

MLA Handbook (7th Edition):

Pattillo, Jeffrey. “Mathematical Foundations and Algorithms for Clique Relaxations in Networks.” 2012. Web. 19 Oct 2020.

Vancouver:

Pattillo J. Mathematical Foundations and Algorithms for Clique Relaxations in Networks. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10540.

Council of Science Editors:

Pattillo J. Mathematical Foundations and Algorithms for Clique Relaxations in Networks. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10540


Texas A&M University

2. Li, Di. Distributed Signal Processing over Large-Scale Complex Systems.

Degree: PhD, Electrical Engineering, 2017, Texas A&M University

 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… (more)

Subjects/Keywords: Signal processing; large system; distributed algorithm; Kalman filtering; quickest detection

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APA (6th Edition):

Li, D. (2017). Distributed Signal Processing over Large-Scale Complex Systems. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161279

Chicago Manual of Style (16th Edition):

Li, Di. “Distributed Signal Processing over Large-Scale Complex Systems.” 2017. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/161279.

MLA Handbook (7th Edition):

Li, Di. “Distributed Signal Processing over Large-Scale Complex Systems.” 2017. Web. 19 Oct 2020.

Vancouver:

Li D. Distributed Signal Processing over Large-Scale Complex Systems. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/161279.

Council of Science Editors:

Li D. Distributed Signal Processing over Large-Scale Complex Systems. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161279


Texas A&M University

3. Liang, Zhongwen. Limited Dependent Variable Correlated Random Coefficient Panel Data Models.

Degree: PhD, Economics, 2012, Texas A&M University

 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… (more)

Subjects/Keywords: Limited dependent variable; Panel data; Nonparametric; Binary response; Truncated; Correlated random coefficient

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APA (6th Edition):

Liang, Z. (2012). Limited Dependent Variable Correlated Random Coefficient Panel Data Models. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11682

Chicago Manual of Style (16th Edition):

Liang, Zhongwen. “Limited Dependent Variable Correlated Random Coefficient Panel Data Models.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11682.

MLA Handbook (7th Edition):

Liang, Zhongwen. “Limited Dependent Variable Correlated Random Coefficient Panel Data Models.” 2012. Web. 19 Oct 2020.

Vancouver:

Liang Z. Limited Dependent Variable Correlated Random Coefficient Panel Data Models. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11682.

Council of Science Editors:

Liang Z. Limited Dependent Variable Correlated Random Coefficient Panel Data Models. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11682


Texas A&M University

4. Zhang, Nan. Adaptive Basis Sampling for Smoothing Splines.

Degree: PhD, Statistics, 2015, Texas A&M University

 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… (more)

Subjects/Keywords: Nonparametric regression; Penalized likelihood; Reproducing kernel Hilbert space

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APA (6th Edition):

Zhang, N. (2015). Adaptive Basis Sampling for Smoothing Splines. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155626

Chicago Manual of Style (16th Edition):

Zhang, Nan. “Adaptive Basis Sampling for Smoothing Splines.” 2015. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/155626.

MLA Handbook (7th Edition):

Zhang, Nan. “Adaptive Basis Sampling for Smoothing Splines.” 2015. Web. 19 Oct 2020.

Vancouver:

Zhang N. Adaptive Basis Sampling for Smoothing Splines. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/155626.

Council of Science Editors:

Zhang N. Adaptive Basis Sampling for Smoothing Splines. [Doctoral Dissertation]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155626


Texas A&M University

5. Goldsmith, Aaron Seth. LASSO Asymptotics For Heavy Tailed Errors.

Degree: PhD, Mathematics, 2015, Texas A&M University

We consider the asymptotic behavior of the l1 regularized least squares estimator (LASSO) for the linear regression model Y=X(beta)+xi with training data (X,Y) in RnxpxRn, true parameter beta in Rp, and observation noise xi in Rn. The LASSO estimator, defined by betahat in argminu in Rp||Xu-Y||2+lambda||u||1 introduces a bias toward 0 to encourage sparse estimates. LASSO has become a staple in the statistician’s breadbasket; it behaves very well and is quickly computed. In the case that xii are i.i.d. with E|xii|alpha<alphat}=t-alpha for some 1<alpha<2, Chatterjee and Lahiri found the exact rate, almost surely, for which the LASSO betahat tends to beta. We consider instead xi I that are i.i.d., possess all moments less than alpha, and eventually nearly follow a Pareto tail P{|xii|>t}=t-alpha Specifically, we only require that the tails of xii to be regularly varying. We center and scale both the quantity inside the arg min and betahat itself to prepare for a CLT. We find conditions that promise both convergence (uniformly over a class of designs X) of the quantity inside the arg min and uniform tightness of the centered, scaled bethahat. Then, we use a standard theorem to pass to uniform convergence of the centered, scaled betahat. Finally, we use a basic inequality to prove rate consistency for betahat when p is allowed to increase with n. Advisors/Committee Members: Zinn, Joel (advisor), Schlumprecht, Thomas (committee member), Rojas, Maurice (committee member), Mueller-Harknett, Ursula (committee member).

Subjects/Keywords: LASSO; Weak Convergence; Regular Variation; Heavy Tails

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APA (6th Edition):

Goldsmith, A. S. (2015). LASSO Asymptotics For Heavy Tailed Errors. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/156229

Chicago Manual of Style (16th Edition):

Goldsmith, Aaron Seth. “LASSO Asymptotics For Heavy Tailed Errors.” 2015. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/156229.

MLA Handbook (7th Edition):

Goldsmith, Aaron Seth. “LASSO Asymptotics For Heavy Tailed Errors.” 2015. Web. 19 Oct 2020.

Vancouver:

Goldsmith AS. LASSO Asymptotics For Heavy Tailed Errors. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/156229.

Council of Science Editors:

Goldsmith AS. LASSO Asymptotics For Heavy Tailed Errors. [Doctoral Dissertation]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/156229


Texas A&M University

6. Yang, Yuping. Central Limit Theorems for Empirical Processes Based on Stochastic Processes.

Degree: PhD, Mathematics, 2013, Texas A&M University

 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… (more)

Subjects/Keywords: Central limit theorem; time dependent data

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APA (6th Edition):

Yang, Y. (2013). Central Limit Theorems for Empirical Processes Based on Stochastic Processes. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151373

Chicago Manual of Style (16th Edition):

Yang, Yuping. “Central Limit Theorems for Empirical Processes Based on Stochastic Processes.” 2013. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/151373.

MLA Handbook (7th Edition):

Yang, Yuping. “Central Limit Theorems for Empirical Processes Based on Stochastic Processes.” 2013. Web. 19 Oct 2020.

Vancouver:

Yang Y. Central Limit Theorems for Empirical Processes Based on Stochastic Processes. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/151373.

Council of Science Editors:

Yang Y. Central Limit Theorems for Empirical Processes Based on Stochastic Processes. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151373


Texas A&M University

7. Chen, Lianfu. Topics on Regularization of Parameters in Multivariate Linear Regression.

Degree: PhD, Statistics, 2012, Texas A&M University

 My dissertation mainly focuses on the regularization of parameters in the multivariate linear regression under different assumptions on the distribution of the errors. It consists… (more)

Subjects/Keywords: Eigenvector; EM algorithm; Lasso regression; Multivariate skew-normal and skew-t: Penalty; Regularization.

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APA (6th Edition):

Chen, L. (2012). Topics on Regularization of Parameters in Multivariate Linear Regression. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10644

Chicago Manual of Style (16th Edition):

Chen, Lianfu. “Topics on Regularization of Parameters in Multivariate Linear Regression.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10644.

MLA Handbook (7th Edition):

Chen, Lianfu. “Topics on Regularization of Parameters in Multivariate Linear Regression.” 2012. Web. 19 Oct 2020.

Vancouver:

Chen L. Topics on Regularization of Parameters in Multivariate Linear Regression. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10644.

Council of Science Editors:

Chen L. Topics on Regularization of Parameters in Multivariate Linear Regression. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10644


Texas A&M University

8. Chown, Justin Andrew. New Approaches in Testing Common Assumptions for Regressions with Missing Data.

Degree: PhD, Statistics, 2014, Texas A&M University

 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… (more)

Subjects/Keywords: nonparametric; regression; empirical distribution function; test for normality; transfer principle; efficient estimator; goodness-of-fit test; heteroskedasticity; weighted empirical process; test for heteroskedasticity; distribution free; martingale transform; residual-based; Brownian motion; Brownian bridge

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APA (6th Edition):

Chown, J. A. (2014). New Approaches in Testing Common Assumptions for Regressions with Missing Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153510

Chicago Manual of Style (16th Edition):

Chown, Justin Andrew. “New Approaches in Testing Common Assumptions for Regressions with Missing Data.” 2014. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/153510.

MLA Handbook (7th Edition):

Chown, Justin Andrew. “New Approaches in Testing Common Assumptions for Regressions with Missing Data.” 2014. Web. 19 Oct 2020.

Vancouver:

Chown JA. New Approaches in Testing Common Assumptions for Regressions with Missing Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/153510.

Council of Science Editors:

Chown JA. New Approaches in Testing Common Assumptions for Regressions with Missing Data. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153510


Texas A&M University

9. Mukhopadhyay, Subhadeep. Nonparametric Inference for High Dimensional Data.

Degree: PhD, Statistics, 2013, Texas A&M University

 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… (more)

Subjects/Keywords: Big data; Quantile; Empirical Likelihood; LP score function; Copula; Nonparametric; Classification; Data Science

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APA (6th Edition):

Mukhopadhyay, S. (2013). Nonparametric Inference for High Dimensional Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/149430

Chicago Manual of Style (16th Edition):

Mukhopadhyay, Subhadeep. “Nonparametric Inference for High Dimensional Data.” 2013. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/149430.

MLA Handbook (7th Edition):

Mukhopadhyay, Subhadeep. “Nonparametric Inference for High Dimensional Data.” 2013. Web. 19 Oct 2020.

Vancouver:

Mukhopadhyay S. Nonparametric Inference for High Dimensional Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/149430.

Council of Science Editors:

Mukhopadhyay S. Nonparametric Inference for High Dimensional Data. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/149430


Texas A&M University

10. Jiang, Xingde. Novel Pattern Recognition Approaches to Identification of Gene-Expression Pathways in Banana Cultivars.

Degree: PhD, Electrical Engineering, 2016, Texas A&M University

 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… (more)

Subjects/Keywords: pattern recognition; naive-Bayes; bolstered error estimation; model selection; RNA-Seq; bioinformatics; banana cultivars; drought stress; pathogen disease; genes and pathways; biotic and abiotic stress; pathway analysis

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APA (6th Edition):

Jiang, X. (2016). Novel Pattern Recognition Approaches to Identification of Gene-Expression Pathways in Banana Cultivars. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/158920

Chicago Manual of Style (16th Edition):

Jiang, Xingde. “Novel Pattern Recognition Approaches to Identification of Gene-Expression Pathways in Banana Cultivars.” 2016. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/158920.

MLA Handbook (7th Edition):

Jiang, Xingde. “Novel Pattern Recognition Approaches to Identification of Gene-Expression Pathways in Banana Cultivars.” 2016. Web. 19 Oct 2020.

Vancouver:

Jiang X. Novel Pattern Recognition Approaches to Identification of Gene-Expression Pathways in Banana Cultivars. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/158920.

Council of Science Editors:

Jiang X. Novel Pattern Recognition Approaches to Identification of Gene-Expression Pathways in Banana Cultivars. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/158920

11. Crawford, Scott. Efficient Estimation in a Regression Model with Missing Responses.

Degree: PhD, Statistics, 2012, Texas A&M University

 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… (more)

Subjects/Keywords: Efficiency; Missing at Random; Regression; Full Imputation

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APA (6th Edition):

Crawford, S. (2012). Efficient Estimation in a Regression Model with Missing Responses. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11396

Chicago Manual of Style (16th Edition):

Crawford, Scott. “Efficient Estimation in a Regression Model with Missing Responses.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11396.

MLA Handbook (7th Edition):

Crawford, Scott. “Efficient Estimation in a Regression Model with Missing Responses.” 2012. Web. 19 Oct 2020.

Vancouver:

Crawford S. Efficient Estimation in a Regression Model with Missing Responses. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11396.

Council of Science Editors:

Crawford S. Efficient Estimation in a Regression Model with Missing Responses. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11396

12. Linz, William Barham. Investigation of a Markov Chain on Ferrers Boards.

Degree: MS, Mathematics, 2016, Texas A&M University

 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… (more)

Subjects/Keywords: Tsetlin Library; ferrers board; Markov chain

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APA (6th Edition):

Linz, W. B. (2016). Investigation of a Markov Chain on Ferrers Boards. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157094

Chicago Manual of Style (16th Edition):

Linz, William Barham. “Investigation of a Markov Chain on Ferrers Boards.” 2016. Masters Thesis, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/157094.

MLA Handbook (7th Edition):

Linz, William Barham. “Investigation of a Markov Chain on Ferrers Boards.” 2016. Web. 19 Oct 2020.

Vancouver:

Linz WB. Investigation of a Markov Chain on Ferrers Boards. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/157094.

Council of Science Editors:

Linz WB. Investigation of a Markov Chain on Ferrers Boards. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157094

13. Ouyang, Desheng. Nonparametric estimation of econometric models with categorical variables.

Degree: PhD, Economics, 2006, Texas A&M University

 In this dissertation I investigate several topics in the field of nonparametric econometrics. In chapter II, we consider the problem of estimating a nonparametric regression… (more)

Subjects/Keywords: NONPARAQMETRIC; CATEGORICAL

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APA (6th Edition):

Ouyang, D. (2006). Nonparametric estimation of econometric models with categorical variables. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/4298

Chicago Manual of Style (16th Edition):

Ouyang, Desheng. “Nonparametric estimation of econometric models with categorical variables.” 2006. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/4298.

MLA Handbook (7th Edition):

Ouyang, Desheng. “Nonparametric estimation of econometric models with categorical variables.” 2006. Web. 19 Oct 2020.

Vancouver:

Ouyang D. Nonparametric estimation of econometric models with categorical variables. [Internet] [Doctoral dissertation]. Texas A&M University; 2006. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/4298.

Council of Science Editors:

Ouyang D. Nonparametric estimation of econometric models with categorical variables. [Doctoral Dissertation]. Texas A&M University; 2006. Available from: http://hdl.handle.net/1969.1/4298

14. Ward, John P. L^p Bernstein Inequalities and Radial Basis Function Approximation.

Degree: PhD, Mathematics, 2012, Texas A&M University

 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… (more)

Subjects/Keywords: radial basis functions; Bernstein inequalities

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APA (6th Edition):

Ward, J. P. (2012). L^p Bernstein Inequalities and Radial Basis Function Approximation. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8404

Chicago Manual of Style (16th Edition):

Ward, John P. “L^p Bernstein Inequalities and Radial Basis Function Approximation.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8404.

MLA Handbook (7th Edition):

Ward, John P. “L^p Bernstein Inequalities and Radial Basis Function Approximation.” 2012. Web. 19 Oct 2020.

Vancouver:

Ward JP. L^p Bernstein Inequalities and Radial Basis Function Approximation. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8404.

Council of Science Editors:

Ward JP. L^p Bernstein Inequalities and Radial Basis Function Approximation. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8404

15. Bailey, Benjamin Aaron. Studies in Interpolation and Approximation of Multivariate Bandlimited Functions.

Degree: PhD, Mathematics, 2012, Texas A&M University

 The focus of this dissertation is the interpolation and approximation of multivariate bandlimited functions via sampled (function) values. The first set of results investigates polynomial… (more)

Subjects/Keywords: bandlimited functions; polynomial interpolation; approximation; oversampling

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APA (6th Edition):

Bailey, B. A. (2012). Studies in Interpolation and Approximation of Multivariate Bandlimited Functions. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9967

Chicago Manual of Style (16th Edition):

Bailey, Benjamin Aaron. “Studies in Interpolation and Approximation of Multivariate Bandlimited Functions.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9967.

MLA Handbook (7th Edition):

Bailey, Benjamin Aaron. “Studies in Interpolation and Approximation of Multivariate Bandlimited Functions.” 2012. Web. 19 Oct 2020.

Vancouver:

Bailey BA. Studies in Interpolation and Approximation of Multivariate Bandlimited Functions. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9967.

Council of Science Editors:

Bailey BA. Studies in Interpolation and Approximation of Multivariate Bandlimited Functions. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9967


Texas A&M University

16. Zheng, Bentuo. Embeddings and factorizations of Banach spaces.

Degree: PhD, Mathematics, 2009, Texas A&M University

 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… (more)

Subjects/Keywords: embeddings; factorizations

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APA (6th Edition):

Zheng, B. (2009). Embeddings and factorizations of Banach spaces. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-1551

Chicago Manual of Style (16th Edition):

Zheng, Bentuo. “Embeddings and factorizations of Banach spaces.” 2009. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-1551.

MLA Handbook (7th Edition):

Zheng, Bentuo. “Embeddings and factorizations of Banach spaces.” 2009. Web. 19 Oct 2020.

Vancouver:

Zheng B. Embeddings and factorizations of Banach spaces. [Internet] [Doctoral dissertation]. Texas A&M University; 2009. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1551.

Council of Science Editors:

Zheng B. Embeddings and factorizations of Banach spaces. [Doctoral Dissertation]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1551


Texas A&M University

17. Boucher, Thomas Richard. V-uniform ergodicity of threshold autoregressive nonlinear time series.

Degree: PhD, Statistics, 2004, Texas A&M University

 We investigate conditions for the ergodicity of threshold autoregressive time series by embedding the time series in a general state Markov chain and apply a… (more)

Subjects/Keywords: ergodicity; V-uniform; nonlinear time series

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APA (6th Edition):

Boucher, T. R. (2004). V-uniform ergodicity of threshold autoregressive nonlinear time series. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/292

Chicago Manual of Style (16th Edition):

Boucher, Thomas Richard. “V-uniform ergodicity of threshold autoregressive nonlinear time series.” 2004. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/292.

MLA Handbook (7th Edition):

Boucher, Thomas Richard. “V-uniform ergodicity of threshold autoregressive nonlinear time series.” 2004. Web. 19 Oct 2020.

Vancouver:

Boucher TR. V-uniform ergodicity of threshold autoregressive nonlinear time series. [Internet] [Doctoral dissertation]. Texas A&M University; 2004. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/292.

Council of Science Editors:

Boucher TR. V-uniform ergodicity of threshold autoregressive nonlinear time series. [Doctoral Dissertation]. Texas A&M University; 2004. Available from: http://hdl.handle.net/1969.1/292


Texas A&M University

18. Song, Juhee. Bootstrapping in a high dimensional but very low sample size problem.

Degree: PhD, Statistics, 2006, Texas A&M University

 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.… (more)

Subjects/Keywords: Bootstrap; Density Estimation; Clustering; High dimensional Data

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Song, J. (2006). Bootstrapping in a high dimensional but very low sample size problem. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/3853

Chicago Manual of Style (16th Edition):

Song, Juhee. “Bootstrapping in a high dimensional but very low sample size problem.” 2006. Doctoral Dissertation, Texas A&M University. Accessed October 19, 2020. http://hdl.handle.net/1969.1/3853.

MLA Handbook (7th Edition):

Song, Juhee. “Bootstrapping in a high dimensional but very low sample size problem.” 2006. Web. 19 Oct 2020.

Vancouver:

Song J. Bootstrapping in a high dimensional but very low sample size problem. [Internet] [Doctoral dissertation]. Texas A&M University; 2006. [cited 2020 Oct 19]. Available from: http://hdl.handle.net/1969.1/3853.

Council of Science Editors:

Song J. Bootstrapping in a high dimensional but very low sample size problem. [Doctoral Dissertation]. Texas A&M University; 2006. Available from: http://hdl.handle.net/1969.1/3853

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