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You searched for +publisher:"Texas A&M University" +contributor:("Carroll, Raymond J."). Showing records 1 – 30 of 51 total matches.

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Texas A&M University

1. Zhu, Xinxin. Wind Speed Forecasting for Power System Operation.

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

 In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and… (more)

Subjects/Keywords: Wind Forecasting; Space-Time

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APA (6th Edition):

Zhu, X. (2013). Wind Speed Forecasting for Power System Operation. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151248

Chicago Manual of Style (16th Edition):

Zhu, Xinxin. “Wind Speed Forecasting for Power System Operation.” 2013. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/151248.

MLA Handbook (7th Edition):

Zhu, Xinxin. “Wind Speed Forecasting for Power System Operation.” 2013. Web. 24 Oct 2020.

Vancouver:

Zhu X. Wind Speed Forecasting for Power System Operation. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/151248.

Council of Science Editors:

Zhu X. Wind Speed Forecasting for Power System Operation. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151248


Texas A&M University

2. Xu, Ganggang. Variable Selection and Function Estimation Using Penalized Methods.

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

 Penalized methods are becoming more and more popular in statistical research. This dissertation research covers two major aspects of applications of penalized methods: variable selection… (more)

Subjects/Keywords: Adaptive lasso; Autoregressive model; Infinite variance; Least absolute deviation; Cross-validation, Generalized estimating equations, Multiple smoothing parameters, Penalized splines, Working covariance matrix.

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APA (6th Edition):

Xu, G. (2012). Variable Selection and Function Estimation Using Penalized Methods. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10451

Chicago Manual of Style (16th Edition):

Xu, Ganggang. “Variable Selection and Function Estimation Using Penalized Methods.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10451.

MLA Handbook (7th Edition):

Xu, Ganggang. “Variable Selection and Function Estimation Using Penalized Methods.” 2012. Web. 24 Oct 2020.

Vancouver:

Xu G. Variable Selection and Function Estimation Using Penalized Methods. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10451.

Council of Science Editors:

Xu G. Variable Selection and Function Estimation Using Penalized Methods. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10451


Texas A&M University

3. Liang, Liang. Semiparametric Efficient Estimators in Primary and Secondary Analysis of Case-Control Studies.

Degree: PhD, Statistics, 2017, Texas A&M University

 As a cost-efficient alternative to cohort design, case-control design is widely used in epidemiological studies. The primary analysis of the case-control studies focuses on the… (more)

Subjects/Keywords: Biased samples; Case-control study; Gene-environment interaction; Primary Analysis; Secondary analysis; Semiparametric estimation; Heteroscedastic errors; Quantile regression

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APA (6th Edition):

Liang, L. (2017). Semiparametric Efficient Estimators in Primary and Secondary Analysis of Case-Control Studies. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161456

Chicago Manual of Style (16th Edition):

Liang, Liang. “Semiparametric Efficient Estimators in Primary and Secondary Analysis of Case-Control Studies.” 2017. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/161456.

MLA Handbook (7th Edition):

Liang, Liang. “Semiparametric Efficient Estimators in Primary and Secondary Analysis of Case-Control Studies.” 2017. Web. 24 Oct 2020.

Vancouver:

Liang L. Semiparametric Efficient Estimators in Primary and Secondary Analysis of Case-Control Studies. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/161456.

Council of Science Editors:

Liang L. Semiparametric Efficient Estimators in Primary and Secondary Analysis of Case-Control Studies. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161456


Texas A&M University

4. Xu, Kun. Semiparametric Estimation and Inference with Mis-measured, Correlated or Mixed Observations, and the Application in Ecology, Medicine and Neurology.

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

 The dissertation considers semiparametric regression models inspired by statistical problems in ecological, medical and neurological studies. In those models, the interest is usually on the… (more)

Subjects/Keywords: Semiparamtric; Capture-recapture; Instrument variable; Huntington's Disease; Measurement error

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APA (6th Edition):

Xu, K. (2013). Semiparametric Estimation and Inference with Mis-measured, Correlated or Mixed Observations, and the Application in Ecology, Medicine and Neurology. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151746

Chicago Manual of Style (16th Edition):

Xu, Kun. “Semiparametric Estimation and Inference with Mis-measured, Correlated or Mixed Observations, and the Application in Ecology, Medicine and Neurology.” 2013. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/151746.

MLA Handbook (7th Edition):

Xu, Kun. “Semiparametric Estimation and Inference with Mis-measured, Correlated or Mixed Observations, and the Application in Ecology, Medicine and Neurology.” 2013. Web. 24 Oct 2020.

Vancouver:

Xu K. Semiparametric Estimation and Inference with Mis-measured, Correlated or Mixed Observations, and the Application in Ecology, Medicine and Neurology. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/151746.

Council of Science Editors:

Xu K. Semiparametric Estimation and Inference with Mis-measured, Correlated or Mixed Observations, and the Application in Ecology, Medicine and Neurology. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151746


Texas A&M University

5. Zhang, Lin. Application of Bayesian Hierarchical Models in Genetic Data Analysis.

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

 Genetic data analysis has been capturing a lot of attentions for understanding the mechanism of the development and progressing of diseases like cancers, and is… (more)

Subjects/Keywords: covariance estimation; feature selection; graphical network modeling; genetic data analysis; Bayesian hierarchical model

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APA (6th Edition):

Zhang, L. (2012). Application of Bayesian Hierarchical Models in Genetic Data Analysis. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/148056

Chicago Manual of Style (16th Edition):

Zhang, Lin. “Application of Bayesian Hierarchical Models in Genetic Data Analysis.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/148056.

MLA Handbook (7th Edition):

Zhang, Lin. “Application of Bayesian Hierarchical Models in Genetic Data Analysis.” 2012. Web. 24 Oct 2020.

Vancouver:

Zhang L. Application of Bayesian Hierarchical Models in Genetic Data Analysis. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/148056.

Council of Science Editors:

Zhang L. Application of Bayesian Hierarchical Models in Genetic Data Analysis. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/148056


Texas A&M University

6. Xun, Xiaolei. Statistical Inference in Inverse Problems.

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

 Inverse problems have gained popularity in statistical research recently. This dissertation consists of two statistical inverse problems: a Bayesian approach to detection of small low… (more)

Subjects/Keywords: Inverse problems; Bayesian method; Source detection; Parameter estimation; Parameter cascading; Partial differential equations.

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APA (6th Edition):

Xun, X. (2012). Statistical Inference in Inverse Problems. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874

Chicago Manual of Style (16th Edition):

Xun, Xiaolei. “Statistical Inference in Inverse Problems.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874.

MLA Handbook (7th Edition):

Xun, Xiaolei. “Statistical Inference in Inverse Problems.” 2012. Web. 24 Oct 2020.

Vancouver:

Xun X. Statistical Inference in Inverse Problems. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874.

Council of Science Editors:

Xun X. Statistical Inference in Inverse Problems. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874


Texas A&M University

7. 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 24, 2020. http://hdl.handle.net/1969.1/155626.

MLA Handbook (7th Edition):

Zhang, Nan. “Adaptive Basis Sampling for Smoothing Splines.” 2015. Web. 24 Oct 2020.

Vancouver:

Zhang N. Adaptive Basis Sampling for Smoothing Splines. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Oct 24]. 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

8. Wang, Tianying. Topics in Measurement Error Analysis and High-Dimensional Binary Classification.

Degree: PhD, Statistics, 2018, Texas A&M University

 We propose novel methods to tackle two problems: the misspecified model with measurement error and high-dimensional binary classification, both have a crucial impact on applications… (more)

Subjects/Keywords: categorization; differential misclassification; epidemiology practice; Inverse problems; measurement error; convex optimization; discriminant analysis; high-dimensional statistics; variable selection

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APA (6th Edition):

Wang, T. (2018). Topics in Measurement Error Analysis and High-Dimensional Binary Classification. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173923

Chicago Manual of Style (16th Edition):

Wang, Tianying. “Topics in Measurement Error Analysis and High-Dimensional Binary Classification.” 2018. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/173923.

MLA Handbook (7th Edition):

Wang, Tianying. “Topics in Measurement Error Analysis and High-Dimensional Binary Classification.” 2018. Web. 24 Oct 2020.

Vancouver:

Wang T. Topics in Measurement Error Analysis and High-Dimensional Binary Classification. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/173923.

Council of Science Editors:

Wang T. Topics in Measurement Error Analysis and High-Dimensional Binary Classification. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173923


Texas A&M University

9. Redd, Andrew Middleton. An Additive Bivariate Hierarchical Model for Functional Data and Related Computations.

Degree: PhD, Statistics, 2011, Texas A&M University

 The work presented in this dissertation centers on the theme of regression and computation methodology. Functional data is an important class of longitudinal data, and… (more)

Subjects/Keywords: Additive Models; Functional Data; Mixed Models; Nonparametric Regression; O-splines; Smoothing Parameter Estimation; Splines; Software Packages

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APA (6th Edition):

Redd, A. M. (2011). An Additive Bivariate Hierarchical Model for Functional Data and Related Computations. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8290

Chicago Manual of Style (16th Edition):

Redd, Andrew Middleton. “An Additive Bivariate Hierarchical Model for Functional Data and Related Computations.” 2011. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8290.

MLA Handbook (7th Edition):

Redd, Andrew Middleton. “An Additive Bivariate Hierarchical Model for Functional Data and Related Computations.” 2011. Web. 24 Oct 2020.

Vancouver:

Redd AM. An Additive Bivariate Hierarchical Model for Functional Data and Related Computations. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8290.

Council of Science Editors:

Redd AM. An Additive Bivariate Hierarchical Model for Functional Data and Related Computations. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8290


Texas A&M University

10. Wei, Rubin. Highly Nonlinear Measurement Error Models in Nutritional Epidemiology.

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

 This dissertation consists of two main projects in the area of measurement error models with application in nutritional epidemiology. The first project studies the application… (more)

Subjects/Keywords: Measurement error; Berkson-type error; Latent variable models; Moment reconstruction; Bayesian methods; Hard zeroes; Zero-inflation; Mixed models; Nutritional epidemiology; Usual intake; Never-consumers

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APA (6th Edition):

Wei, R. (2014). Highly Nonlinear Measurement Error Models in Nutritional Epidemiology. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161236

Chicago Manual of Style (16th Edition):

Wei, Rubin. “Highly Nonlinear Measurement Error Models in Nutritional Epidemiology.” 2014. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/161236.

MLA Handbook (7th Edition):

Wei, Rubin. “Highly Nonlinear Measurement Error Models in Nutritional Epidemiology.” 2014. Web. 24 Oct 2020.

Vancouver:

Wei R. Highly Nonlinear Measurement Error Models in Nutritional Epidemiology. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/161236.

Council of Science Editors:

Wei R. Highly Nonlinear Measurement Error Models in Nutritional Epidemiology. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/161236


Texas A&M University

11. Lee, Donghyuk. Testing Statistical Hypotheses for Latent Variable Models and Some Computational Issues.

Degree: PhD, Statistics, 2018, Texas A&M University

 In this dissertation, I address unorthodox statistical problems concerning goodness-of-fit tests in the latent variable context and efficient statistical computations. In epidemiological and biomedical studies… (more)

Subjects/Keywords: Bootstrap; Goodness-of-fit; Standard error; Skew-probit link; Technical inefficiency; Two sample test

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APA (6th Edition):

Lee, D. (2018). Testing Statistical Hypotheses for Latent Variable Models and Some Computational Issues. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173973

Chicago Manual of Style (16th Edition):

Lee, Donghyuk. “Testing Statistical Hypotheses for Latent Variable Models and Some Computational Issues.” 2018. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/173973.

MLA Handbook (7th Edition):

Lee, Donghyuk. “Testing Statistical Hypotheses for Latent Variable Models and Some Computational Issues.” 2018. Web. 24 Oct 2020.

Vancouver:

Lee D. Testing Statistical Hypotheses for Latent Variable Models and Some Computational Issues. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/173973.

Council of Science Editors:

Lee D. Testing Statistical Hypotheses for Latent Variable Models and Some Computational Issues. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173973


Texas A&M University

12. Sun, Ranye. Thresholding Multivariate Regression and Generalized Principal Components.

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

 As high-dimensional data arises from various fields in science and technology, traditional multivariate methods need to be updated. Principal component analysis and reduced rank regression… (more)

Subjects/Keywords: cross-validation; iterative subspace projections; low-rank matrix approximation; regularization; transposable data.

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APA (6th Edition):

Sun, R. (2014). Thresholding Multivariate Regression and Generalized Principal Components. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/152564

Chicago Manual of Style (16th Edition):

Sun, Ranye. “Thresholding Multivariate Regression and Generalized Principal Components.” 2014. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/152564.

MLA Handbook (7th Edition):

Sun, Ranye. “Thresholding Multivariate Regression and Generalized Principal Components.” 2014. Web. 24 Oct 2020.

Vancouver:

Sun R. Thresholding Multivariate Regression and Generalized Principal Components. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/152564.

Council of Science Editors:

Sun R. Thresholding Multivariate Regression and Generalized Principal Components. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/152564


Texas A&M University

13. Sarkar, Abhra. Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors.

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

 Although the literature on measurement error problems is quite extensive, solutions to even the most fundamental measurement error problems like density deconvolution and regression with… (more)

Subjects/Keywords: B-splines; Conditional heteroscedasticity; Density deconvolution; Dirichlet process; Latent factor analyzers; Measurement errors; Mixture models; Nutritional epidemiology; Regression with errors in covariates; Sparsity inducing priors

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APA (6th Edition):

Sarkar, A. (2014). Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153327

Chicago Manual of Style (16th Edition):

Sarkar, Abhra. “Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors.” 2014. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/153327.

MLA Handbook (7th Edition):

Sarkar, Abhra. “Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors.” 2014. Web. 24 Oct 2020.

Vancouver:

Sarkar A. Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/153327.

Council of Science Editors:

Sarkar A. Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153327


Texas A&M University

14. 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 24, 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. 24 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 24]. 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

15. McGuffey, Elizabeth Jennings. Statistical Methods for Integrating Genomics Data.

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

 This dissertation focuses on methodology to integrate multiplatform genomic data with cancer applications. Such integration facilitates the discovery of biological information crucial to the development… (more)

Subjects/Keywords: Bayesian modeling; Genomics; Heatmaps; Hierarchical models; Integrative analysis; Shrinkage priors; TCGA

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APA (6th Edition):

McGuffey, E. J. (2015). Statistical Methods for Integrating Genomics Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155093

Chicago Manual of Style (16th Edition):

McGuffey, Elizabeth Jennings. “Statistical Methods for Integrating Genomics Data.” 2015. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/155093.

MLA Handbook (7th Edition):

McGuffey, Elizabeth Jennings. “Statistical Methods for Integrating Genomics Data.” 2015. Web. 24 Oct 2020.

Vancouver:

McGuffey EJ. Statistical Methods for Integrating Genomics Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/155093.

Council of Science Editors:

McGuffey EJ. Statistical Methods for Integrating Genomics Data. [Doctoral Dissertation]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155093


Texas A&M University

16. Goddard, Scott D. Restricted Most Powerful Bayesian Tests.

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

 Uniformly most powerful Bayesian tests (UMPBTs) are defined to be Bayesian tests that maximize the probability that the Bayes factor against a fixed null hypothesis… (more)

Subjects/Keywords: Hypothesis tests; g prior; UMPBT; Bayesian variable selection

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APA (6th Edition):

Goddard, S. D. (2015). Restricted Most Powerful Bayesian Tests. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155108

Chicago Manual of Style (16th Edition):

Goddard, Scott D. “Restricted Most Powerful Bayesian Tests.” 2015. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/155108.

MLA Handbook (7th Edition):

Goddard, Scott D. “Restricted Most Powerful Bayesian Tests.” 2015. Web. 24 Oct 2020.

Vancouver:

Goddard SD. Restricted Most Powerful Bayesian Tests. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/155108.

Council of Science Editors:

Goddard SD. Restricted Most Powerful Bayesian Tests. [Doctoral Dissertation]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155108


Texas A&M University

17. Asher, Alexander Allen. Semiparametric Analysis of Complex Polygenic Gene-Environment Interactions in Case-Control Studies.

Degree: PhD, Statistics, 2018, Texas A&M University

 Gene-environment interactions can be efficiently estimated in case-control data by existing retrospective methods that assume gene-environment independence in the source population, but such techniques require… (more)

Subjects/Keywords: Case-control studies; Gene-environment interactions; Genetic epidemiology; Pseudolikelihood; Retrospective studies; Semiparametric methods

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APA (6th Edition):

Asher, A. A. (2018). Semiparametric Analysis of Complex Polygenic Gene-Environment Interactions in Case-Control Studies. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174127

Chicago Manual of Style (16th Edition):

Asher, Alexander Allen. “Semiparametric Analysis of Complex Polygenic Gene-Environment Interactions in Case-Control Studies.” 2018. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/174127.

MLA Handbook (7th Edition):

Asher, Alexander Allen. “Semiparametric Analysis of Complex Polygenic Gene-Environment Interactions in Case-Control Studies.” 2018. Web. 24 Oct 2020.

Vancouver:

Asher AA. Semiparametric Analysis of Complex Polygenic Gene-Environment Interactions in Case-Control Studies. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/174127.

Council of Science Editors:

Asher AA. Semiparametric Analysis of Complex Polygenic Gene-Environment Interactions in Case-Control Studies. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174127


Texas A&M University

18. Gautam, Raju. Epidemiology of Bacterial Food-borne Pathogens: Linking Intermittent Pathogen Shedding and Transmission in Their Animal Hosts.

Degree: PhD, Biomedical Sciences, 2013, Texas A&M University

 Most bacterial foodborne pathogens are shed intermittently from their animal hosts and are able to grow and persist in the environment. Cattle and pigs constitute… (more)

Subjects/Keywords: Intermittent shedding; environmental persistence; Escherichia coli O157:H7; Salmonella Typhimurium

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APA (6th Edition):

Gautam, R. (2013). Epidemiology of Bacterial Food-borne Pathogens: Linking Intermittent Pathogen Shedding and Transmission in Their Animal Hosts. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/149510

Chicago Manual of Style (16th Edition):

Gautam, Raju. “Epidemiology of Bacterial Food-borne Pathogens: Linking Intermittent Pathogen Shedding and Transmission in Their Animal Hosts.” 2013. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/149510.

MLA Handbook (7th Edition):

Gautam, Raju. “Epidemiology of Bacterial Food-borne Pathogens: Linking Intermittent Pathogen Shedding and Transmission in Their Animal Hosts.” 2013. Web. 24 Oct 2020.

Vancouver:

Gautam R. Epidemiology of Bacterial Food-borne Pathogens: Linking Intermittent Pathogen Shedding and Transmission in Their Animal Hosts. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/149510.

Council of Science Editors:

Gautam R. Epidemiology of Bacterial Food-borne Pathogens: Linking Intermittent Pathogen Shedding and Transmission in Their Animal Hosts. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/149510


Texas A&M University

19. Cho, Young Mi. Colon Cancer Chemoprotection through Epigenetic Effects of a Fish Oil/Pectin Diet.

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

 Accumulated genetic and epigenetic abnormalities contribute to the development of colon cancer. We have shown that a combination of fish oil (containing decosahexaenoic acid, DHA,… (more)

Subjects/Keywords: Fish oil; Pectin; Colon cancer; Epigenetics; DNA methylation; Chemoprotection; Apoptosis

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APA (6th Edition):

Cho, Y. M. (2012). Colon Cancer Chemoprotection through Epigenetic Effects of a Fish Oil/Pectin Diet. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11480

Chicago Manual of Style (16th Edition):

Cho, Young Mi. “Colon Cancer Chemoprotection through Epigenetic Effects of a Fish Oil/Pectin Diet.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11480.

MLA Handbook (7th Edition):

Cho, Young Mi. “Colon Cancer Chemoprotection through Epigenetic Effects of a Fish Oil/Pectin Diet.” 2012. Web. 24 Oct 2020.

Vancouver:

Cho YM. Colon Cancer Chemoprotection through Epigenetic Effects of a Fish Oil/Pectin Diet. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11480.

Council of Science Editors:

Cho YM. Colon Cancer Chemoprotection through Epigenetic Effects of a Fish Oil/Pectin Diet. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11480


Texas A&M University

20. Rahman, Shahina. Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies.

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

 Regression Analysis is one of the most important tools of statistics which is widely used in other scientific fields for projection and modeling of association… (more)

Subjects/Keywords: Bayesian Methods; Case-control; Dirichlet Process of Mixture Model; Efficiency; Heteroscedasticity; Kernel estimation; Nonparametric; P-splines; Robust; Secondary Analysis; Semiparametric; Single-Index Model

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APA (6th Edition):

Rahman, S. (2015). Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155719

Chicago Manual of Style (16th Edition):

Rahman, Shahina. “Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies.” 2015. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/155719.

MLA Handbook (7th Edition):

Rahman, Shahina. “Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies.” 2015. Web. 24 Oct 2020.

Vancouver:

Rahman S. Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/155719.

Council of Science Editors:

Rahman S. Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies. [Doctoral Dissertation]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155719

21. Zhong, Ming. Extended Homozygosity Score Tests to Detect Positive Selection in Genome-wide Scans.

Degree: PhD, Statistics, 2011, Texas A&M University

 Positive natural selection is recognized as the driving force underneath evolution. One of the surest signatures of recent positive selection is a local elevation of… (more)

Subjects/Keywords: Extended homozygosity; linkage disequilibrium; positive selection.

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APA (6th Edition):

Zhong, M. (2011). Extended Homozygosity Score Tests to Detect Positive Selection in Genome-wide Scans. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7687

Chicago Manual of Style (16th Edition):

Zhong, Ming. “Extended Homozygosity Score Tests to Detect Positive Selection in Genome-wide Scans.” 2011. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7687.

MLA Handbook (7th Edition):

Zhong, Ming. “Extended Homozygosity Score Tests to Detect Positive Selection in Genome-wide Scans.” 2011. Web. 24 Oct 2020.

Vancouver:

Zhong M. Extended Homozygosity Score Tests to Detect Positive Selection in Genome-wide Scans. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7687.

Council of Science Editors:

Zhong M. Extended Homozygosity Score Tests to Detect Positive Selection in Genome-wide Scans. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7687

22. Garcia, Tanya. Efficient Semiparametric Estimators for Biological, Genetic, and Measurement Error Applications.

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

 Many statistical models, like measurement error models, a general class of survival models, and a mixture data model with random censoring, are semiparametric where interest… (more)

Subjects/Keywords: Measurement Error; Mixture data; Nonproportional hazards model; Semiparametric Methods

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APA (6th Edition):

Garcia, T. (2012). Efficient Semiparametric Estimators for Biological, Genetic, and Measurement Error Applications. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9700

Chicago Manual of Style (16th Edition):

Garcia, Tanya. “Efficient Semiparametric Estimators for Biological, Genetic, and Measurement Error Applications.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9700.

MLA Handbook (7th Edition):

Garcia, Tanya. “Efficient Semiparametric Estimators for Biological, Genetic, and Measurement Error Applications.” 2012. Web. 24 Oct 2020.

Vancouver:

Garcia T. Efficient Semiparametric Estimators for Biological, Genetic, and Measurement Error Applications. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9700.

Council of Science Editors:

Garcia T. Efficient Semiparametric Estimators for Biological, Genetic, and Measurement Error Applications. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9700

23. Singh, Trijya. Efficient Small Area Estimation in the Presence of Measurement Error in Covariates.

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

 Small area estimation is an arena that has seen rapid development in the past 50 years, due to its widespread applicability in government projects, marketing… (more)

Subjects/Keywords: Covariates; Measurement Error; SIMEX; Small Area Estimation; Corrected Scores

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APA (6th Edition):

Singh, T. (2012). Efficient Small Area Estimation in the Presence of Measurement Error in Covariates. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-10010

Chicago Manual of Style (16th Edition):

Singh, Trijya. “Efficient Small Area Estimation in the Presence of Measurement Error in Covariates.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-10010.

MLA Handbook (7th Edition):

Singh, Trijya. “Efficient Small Area Estimation in the Presence of Measurement Error in Covariates.” 2012. Web. 24 Oct 2020.

Vancouver:

Singh T. Efficient Small Area Estimation in the Presence of Measurement Error in Covariates. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-10010.

Council of Science Editors:

Singh T. Efficient Small Area Estimation in the Presence of Measurement Error in Covariates. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-10010

24. Ryu, Duchwan. Regression analysis with longitudinal measurements.

Degree: PhD, Statistics, 2005, Texas A&M University

 Bayesian approaches to the regression analysis for longitudinal measurements are considered. The history of measurements from a subject may convey characteristics of the subject. Hence,… (more)

Subjects/Keywords: Bayesian Smoothing Spline; Generalized Additive Model; Measurement Error; Outcome-Dependent Follow-Up; Conditional Predictive Ordinate

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APA (6th Edition):

Ryu, D. (2005). Regression analysis with longitudinal measurements. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/2398

Chicago Manual of Style (16th Edition):

Ryu, Duchwan. “Regression analysis with longitudinal measurements.” 2005. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/2398.

MLA Handbook (7th Edition):

Ryu, Duchwan. “Regression analysis with longitudinal measurements.” 2005. Web. 24 Oct 2020.

Vancouver:

Ryu D. Regression analysis with longitudinal measurements. [Internet] [Doctoral dissertation]. Texas A&M University; 2005. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/2398.

Council of Science Editors:

Ryu D. Regression analysis with longitudinal measurements. [Doctoral Dissertation]. Texas A&M University; 2005. Available from: http://hdl.handle.net/1969.1/2398

25. Bandyopadhyay, Soutir. On Parametric and Nonparametric Methods for Dependent Data.

Degree: PhD, Statistics, 2011, Texas A&M University

 In recent years, there has been a surge of research interest in the analysis of time series and spatial data. While on one hand more… (more)

Subjects/Keywords: Bootstrap; Mean squared prediction error; second order bias correction; tilting; Asymptotic independence; Central limit theorem; DFT; Random field; Spatial processes; Spatial design.

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APA (6th Edition):

Bandyopadhyay, S. (2011). On Parametric and Nonparametric Methods for Dependent Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8277

Chicago Manual of Style (16th Edition):

Bandyopadhyay, Soutir. “On Parametric and Nonparametric Methods for Dependent Data.” 2011. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8277.

MLA Handbook (7th Edition):

Bandyopadhyay, Soutir. “On Parametric and Nonparametric Methods for Dependent Data.” 2011. Web. 24 Oct 2020.

Vancouver:

Bandyopadhyay S. On Parametric and Nonparametric Methods for Dependent Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8277.

Council of Science Editors:

Bandyopadhyay S. On Parametric and Nonparametric Methods for Dependent Data. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8277

26. Lennox, Kristin Patricia. Bayesian Nonparametric Methods for Protein Structure Prediction.

Degree: PhD, Statistics, 2011, Texas A&M University

 The protein structure prediction problem consists of determining a protein’s three-dimensional structure from the underlying sequence of amino acids. A standard approach for predicting such… (more)

Subjects/Keywords: Bayesian statistics; Nonparametric statistics; Density esitimation; Angular data

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APA (6th Edition):

Lennox, K. P. (2011). Bayesian Nonparametric Methods for Protein Structure Prediction. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8226

Chicago Manual of Style (16th Edition):

Lennox, Kristin Patricia. “Bayesian Nonparametric Methods for Protein Structure Prediction.” 2011. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8226.

MLA Handbook (7th Edition):

Lennox, Kristin Patricia. “Bayesian Nonparametric Methods for Protein Structure Prediction.” 2011. Web. 24 Oct 2020.

Vancouver:

Lennox KP. Bayesian Nonparametric Methods for Protein Structure Prediction. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8226.

Council of Science Editors:

Lennox KP. Bayesian Nonparametric Methods for Protein Structure Prediction. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8226

27. Wei, Jiawei. Secondary Analysis of Case-Control Studies in Genomic Contexts.

Degree: PhD, Statistics, 2011, Texas A&M University

 This dissertation consists of five independent projects. In each project, a novel statistical method was developed to address a practical problem encountered in genomic contexts.… (more)

Subjects/Keywords: Semiparametric Regression; Case-Control; Score Test; Model Selection; Classification

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APA (6th Edition):

Wei, J. (2011). Secondary Analysis of Case-Control Studies in Genomic Contexts. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8269

Chicago Manual of Style (16th Edition):

Wei, Jiawei. “Secondary Analysis of Case-Control Studies in Genomic Contexts.” 2011. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8269.

MLA Handbook (7th Edition):

Wei, Jiawei. “Secondary Analysis of Case-Control Studies in Genomic Contexts.” 2011. Web. 24 Oct 2020.

Vancouver:

Wei J. Secondary Analysis of Case-Control Studies in Genomic Contexts. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8269.

Council of Science Editors:

Wei J. Secondary Analysis of Case-Control Studies in Genomic Contexts. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8269

28. Sun, Ying. Inference and Visualization of Periodic Sequences.

Degree: PhD, Statistics, 2011, Texas A&M University

 This dissertation is composed of four articles describing inference and visualization of periodic sequences. In the first article, a nonparametric method is proposed for estimating… (more)

Subjects/Keywords: Functional Boxplots; Nonparametric Estimation; Outlier Detection; Period Estimation; Space-time Data; Visualization

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APA (6th Edition):

Sun, Y. (2011). Inference and Visualization of Periodic Sequences. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9839

Chicago Manual of Style (16th Edition):

Sun, Ying. “Inference and Visualization of Periodic Sequences.” 2011. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9839.

MLA Handbook (7th Edition):

Sun, Ying. “Inference and Visualization of Periodic Sequences.” 2011. Web. 24 Oct 2020.

Vancouver:

Sun Y. Inference and Visualization of Periodic Sequences. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9839.

Council of Science Editors:

Sun Y. Inference and Visualization of Periodic Sequences. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9839

29. Dhavala, Soma Sekhar. Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression.

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

 We are concerned with testing for differential expression and consider three different aspects of such testing procedures. First, we develop an exact ANOVA type model… (more)

Subjects/Keywords: Bayesian Models; Generalized linear models; Semiparametric models; Dirichlet process; Meta-analysis; Multiple hypothesis testing; Bioinformatics

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APA (6th Edition):

Dhavala, S. S. (2012). Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659

Chicago Manual of Style (16th Edition):

Dhavala, Soma Sekhar. “Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression.” 2012. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659.

MLA Handbook (7th Edition):

Dhavala, Soma Sekhar. “Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression.” 2012. Web. 24 Oct 2020.

Vancouver:

Dhavala SS. Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659.

Council of Science Editors:

Dhavala SS. Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659

30. Ball, Robyn Lynn. Statistical Methods for High Dimensional Biomedical Data.

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

 This dissertation consists of four different topics in the areas of proteomics, genomics, and cardiology. First, a data-based method was developed to assign the subcellular… (more)

Subjects/Keywords: Proteomics; Subcellular Localization; Genomics; Cardiology; Statistics; Biostatistics

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APA (6th Edition):

Ball, R. L. (2013). Statistical Methods for High Dimensional Biomedical Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/149375

Chicago Manual of Style (16th Edition):

Ball, Robyn Lynn. “Statistical Methods for High Dimensional Biomedical Data.” 2013. Doctoral Dissertation, Texas A&M University. Accessed October 24, 2020. http://hdl.handle.net/1969.1/149375.

MLA Handbook (7th Edition):

Ball, Robyn Lynn. “Statistical Methods for High Dimensional Biomedical Data.” 2013. Web. 24 Oct 2020.

Vancouver:

Ball RL. Statistical Methods for High Dimensional Biomedical Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1969.1/149375.

Council of Science Editors:

Ball RL. Statistical Methods for High Dimensional Biomedical Data. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/149375

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