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You searched for +publisher:"Virginia Tech" +contributor:("Smith, Eric P."). Showing records 1 – 30 of 97 total matches.

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Virginia Tech

1. Zhang, Angang. Some Advances in Classifying and Modeling Complex Data.

Degree: PhD, Statistics, 2015, Virginia Tech

 In statistical methodology of analyzing data, two of the most commonly used techniques are classification and regression modeling. As scientific technology progresses rapidly, complex data… (more)

Subjects/Keywords: A/B testing; fraud detection; linear classifier; misclassification error; net profit value; reject inference; sparse linear discriminant analysis; two-class classification; variance component mixed model.

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APA (6th Edition):

Zhang, A. (2015). Some Advances in Classifying and Modeling Complex Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/77958

Chicago Manual of Style (16th Edition):

Zhang, Angang. “Some Advances in Classifying and Modeling Complex Data.” 2015. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/77958.

MLA Handbook (7th Edition):

Zhang, Angang. “Some Advances in Classifying and Modeling Complex Data.” 2015. Web. 19 Oct 2019.

Vancouver:

Zhang A. Some Advances in Classifying and Modeling Complex Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/77958.

Council of Science Editors:

Zhang A. Some Advances in Classifying and Modeling Complex Data. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/77958


Virginia Tech

2. Fry, James Thomas. Hierarchical Gaussian Processes for Spatially Dependent Model Selection.

Degree: PhD, Statistics, 2018, Virginia Tech

 In this dissertation, we develop a model selection and estimation methodology for nonstationary spatial fields. Large, spatially correlated data often cover a vast geographical area.… (more)

Subjects/Keywords: spatial statistics; Gaussian process; model selection; nonstationary process; Ising distribution; CAR model

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APA (6th Edition):

Fry, J. T. (2018). Hierarchical Gaussian Processes for Spatially Dependent Model Selection. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/84161

Chicago Manual of Style (16th Edition):

Fry, James Thomas. “Hierarchical Gaussian Processes for Spatially Dependent Model Selection.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/84161.

MLA Handbook (7th Edition):

Fry, James Thomas. “Hierarchical Gaussian Processes for Spatially Dependent Model Selection.” 2018. Web. 19 Oct 2019.

Vancouver:

Fry JT. Hierarchical Gaussian Processes for Spatially Dependent Model Selection. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/84161.

Council of Science Editors:

Fry JT. Hierarchical Gaussian Processes for Spatially Dependent Model Selection. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/84161

3. Bedair, Khaled Farag Emam. Statistical Methods for Multi-type Recurrent Event Data Based on Monte Carlo EM Algorithms and Copula Frailties.

Degree: PhD, Statistics, 2014, Virginia Tech

 In this dissertation, we are interested in studying processes which generate events repeatedly over the follow-up time of a given subject. Such processes are called… (more)

Subjects/Keywords: MCEM algorithm; cancer studies; multi-type recurrent events; multivariate frailty; semiparametric model; random effects; copula; survival analysis.

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APA (6th Edition):

Bedair, K. F. E. (2014). Statistical Methods for Multi-type Recurrent Event Data Based on Monte Carlo EM Algorithms and Copula Frailties. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64981

Chicago Manual of Style (16th Edition):

Bedair, Khaled Farag Emam. “Statistical Methods for Multi-type Recurrent Event Data Based on Monte Carlo EM Algorithms and Copula Frailties.” 2014. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/64981.

MLA Handbook (7th Edition):

Bedair, Khaled Farag Emam. “Statistical Methods for Multi-type Recurrent Event Data Based on Monte Carlo EM Algorithms and Copula Frailties.” 2014. Web. 19 Oct 2019.

Vancouver:

Bedair KFE. Statistical Methods for Multi-type Recurrent Event Data Based on Monte Carlo EM Algorithms and Copula Frailties. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/64981.

Council of Science Editors:

Bedair KFE. Statistical Methods for Multi-type Recurrent Event Data Based on Monte Carlo EM Algorithms and Copula Frailties. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64981


Virginia Tech

4. Velasco-Cruz, Ciro. Spatially Correlated Model Selection (SCOMS).

Degree: PhD, Statistics, 2012, Virginia Tech

 In this dissertation, a variable selection method for spatial data is developed. It is assumed that the spatial process is non-stationary as a whole but… (more)

Subjects/Keywords: Spatial statistics; Ising prior; Non-stationary spatial fields; Variable Selection

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APA (6th Edition):

Velasco-Cruz, C. (2012). Spatially Correlated Model Selection (SCOMS). (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/27791

Chicago Manual of Style (16th Edition):

Velasco-Cruz, Ciro. “Spatially Correlated Model Selection (SCOMS).” 2012. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/27791.

MLA Handbook (7th Edition):

Velasco-Cruz, Ciro. “Spatially Correlated Model Selection (SCOMS).” 2012. Web. 19 Oct 2019.

Vancouver:

Velasco-Cruz C. Spatially Correlated Model Selection (SCOMS). [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/27791.

Council of Science Editors:

Velasco-Cruz C. Spatially Correlated Model Selection (SCOMS). [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/27791


Virginia Tech

5. Duggins, Jonathan William. Parametric Resampling Methods for Retrospective Changepoint Analysis.

Degree: PhD, Statistics, 2010, Virginia Tech

 Changepoint analysis is a useful tool in environmental statistics in that it provides a methodology for threshold detection and modeling processes subject to periodic changes… (more)

Subjects/Keywords: changepoint; bootstrapping; resampling; threshold detection; frequentist

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APA (6th Edition):

Duggins, J. W. (2010). Parametric Resampling Methods for Retrospective Changepoint Analysis. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28146

Chicago Manual of Style (16th Edition):

Duggins, Jonathan William. “Parametric Resampling Methods for Retrospective Changepoint Analysis.” 2010. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/28146.

MLA Handbook (7th Edition):

Duggins, Jonathan William. “Parametric Resampling Methods for Retrospective Changepoint Analysis.” 2010. Web. 19 Oct 2019.

Vancouver:

Duggins JW. Parametric Resampling Methods for Retrospective Changepoint Analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/28146.

Council of Science Editors:

Duggins JW. Parametric Resampling Methods for Retrospective Changepoint Analysis. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/28146


Virginia Tech

6. Vincent, Matthew Timothy. Estimability of natural mortality within a statistical catch-at-age model : a framework and simulation study based on Gulf of Mexico red snapper.

Degree: MS, Fisheries and Wildlife Sciences, 2013, Virginia Tech

 Estimation of natural mortality within statistical catch-at-age models has been relatively unsuccessful and is uncommon within stock assessments. The models I created estimated population-dynamics parameters,… (more)

Subjects/Keywords: red snapper; Lutjanus campechanus; natural mortality; statistical catch-at-age model; stock assessment; population dynamics

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APA (6th Edition):

Vincent, M. T. (2013). Estimability of natural mortality within a statistical catch-at-age model : a framework and simulation study based on Gulf of Mexico red snapper. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/52244

Chicago Manual of Style (16th Edition):

Vincent, Matthew Timothy. “Estimability of natural mortality within a statistical catch-at-age model : a framework and simulation study based on Gulf of Mexico red snapper.” 2013. Masters Thesis, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/52244.

MLA Handbook (7th Edition):

Vincent, Matthew Timothy. “Estimability of natural mortality within a statistical catch-at-age model : a framework and simulation study based on Gulf of Mexico red snapper.” 2013. Web. 19 Oct 2019.

Vancouver:

Vincent MT. Estimability of natural mortality within a statistical catch-at-age model : a framework and simulation study based on Gulf of Mexico red snapper. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/52244.

Council of Science Editors:

Vincent MT. Estimability of natural mortality within a statistical catch-at-age model : a framework and simulation study based on Gulf of Mexico red snapper. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/52244


Virginia Tech

7. Schilling, Daniel Edward. Assessment of morphological and molecular genetic variation of freshwater mussel species belonging to the genera Fusconaia, Pleurobema, and Pleuronaia in the upper Tennessee River basin.

Degree: MS, Fisheries and Wildlife Sciences, 2015, Virginia Tech

 Select freshwater mussels in the genera Fusconaia, Pleurobema, and Pleuronaia were collected primarily in the upper Tennessee River basin from 2012 to 2014 for phylogenetic… (more)

Subjects/Keywords: Freshwater Mussels; Fusconaia; Pleurobema; Pleuronaia; Molecular Genetics; Morphometrics; Geometric Morphometrics; Dichotomous Key

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APA (6th Edition):

Schilling, D. E. (2015). Assessment of morphological and molecular genetic variation of freshwater mussel species belonging to the genera Fusconaia, Pleurobema, and Pleuronaia in the upper Tennessee River basin. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/54030

Chicago Manual of Style (16th Edition):

Schilling, Daniel Edward. “Assessment of morphological and molecular genetic variation of freshwater mussel species belonging to the genera Fusconaia, Pleurobema, and Pleuronaia in the upper Tennessee River basin.” 2015. Masters Thesis, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/54030.

MLA Handbook (7th Edition):

Schilling, Daniel Edward. “Assessment of morphological and molecular genetic variation of freshwater mussel species belonging to the genera Fusconaia, Pleurobema, and Pleuronaia in the upper Tennessee River basin.” 2015. Web. 19 Oct 2019.

Vancouver:

Schilling DE. Assessment of morphological and molecular genetic variation of freshwater mussel species belonging to the genera Fusconaia, Pleurobema, and Pleuronaia in the upper Tennessee River basin. [Internet] [Masters thesis]. Virginia Tech; 2015. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/54030.

Council of Science Editors:

Schilling DE. Assessment of morphological and molecular genetic variation of freshwater mussel species belonging to the genera Fusconaia, Pleurobema, and Pleuronaia in the upper Tennessee River basin. [Masters Thesis]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/54030


Virginia Tech

8. Wang, Sai. GLR Control Charts for Monitoring the Mean Vector or the Dispersion of a Multivariate Normal Process.

Degree: PhD, Statistics, 2012, Virginia Tech

 In many applications, the quality of process outputs is described by more than one characteristic variable. These quality variables usually follow a multivariate normal (MN)… (more)

Subjects/Keywords: Surveillance; Statistical process control; Quality control; Multivariate EWMA; Multivariate CUSUM; Generalized likelihood ratio; Change point; Covariance

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APA (6th Edition):

Wang, S. (2012). GLR Control Charts for Monitoring the Mean Vector or the Dispersion of a Multivariate Normal Process. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/77227

Chicago Manual of Style (16th Edition):

Wang, Sai. “GLR Control Charts for Monitoring the Mean Vector or the Dispersion of a Multivariate Normal Process.” 2012. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/77227.

MLA Handbook (7th Edition):

Wang, Sai. “GLR Control Charts for Monitoring the Mean Vector or the Dispersion of a Multivariate Normal Process.” 2012. Web. 19 Oct 2019.

Vancouver:

Wang S. GLR Control Charts for Monitoring the Mean Vector or the Dispersion of a Multivariate Normal Process. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/77227.

Council of Science Editors:

Wang S. GLR Control Charts for Monitoring the Mean Vector or the Dispersion of a Multivariate Normal Process. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/77227


Virginia Tech

9. Wang, Lu. Cure Rate Model with Spline Estimated Components.

Degree: PhD, Statistics, 2010, Virginia Tech

 In some survival analysis of medical studies, there are often long term survivors who can be considered as permanently cured. The goals in these studies… (more)

Subjects/Keywords: Nonparametric Function Estimation; Smoothing Splin

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APA (6th Edition):

Wang, L. (2010). Cure Rate Model with Spline Estimated Components. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28359

Chicago Manual of Style (16th Edition):

Wang, Lu. “Cure Rate Model with Spline Estimated Components.” 2010. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/28359.

MLA Handbook (7th Edition):

Wang, Lu. “Cure Rate Model with Spline Estimated Components.” 2010. Web. 19 Oct 2019.

Vancouver:

Wang L. Cure Rate Model with Spline Estimated Components. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/28359.

Council of Science Editors:

Wang L. Cure Rate Model with Spline Estimated Components. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/28359


Virginia Tech

10. Han, Chao. Bayesian Visual Analytics: Interactive Visualization for High Dimensional Data.

Degree: PhD, Statistics, 2012, Virginia Tech

 In light of advancements made in data collection techniques over the past two decades, data mining has become common practice to summarize large, high dimensional… (more)

Subjects/Keywords: Visual Analytics; Bayesian Methods; Dimension Reduction; Human-computer Interaction

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APA (6th Edition):

Han, C. (2012). Bayesian Visual Analytics: Interactive Visualization for High Dimensional Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19210

Chicago Manual of Style (16th Edition):

Han, Chao. “Bayesian Visual Analytics: Interactive Visualization for High Dimensional Data.” 2012. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/19210.

MLA Handbook (7th Edition):

Han, Chao. “Bayesian Visual Analytics: Interactive Visualization for High Dimensional Data.” 2012. Web. 19 Oct 2019.

Vancouver:

Han C. Bayesian Visual Analytics: Interactive Visualization for High Dimensional Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/19210.

Council of Science Editors:

Han C. Bayesian Visual Analytics: Interactive Visualization for High Dimensional Data. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/19210


Virginia Tech

11. Williams, Matthew Richard. Likelihood-based testing and model selection for hazard functions with unknown change-points.

Degree: PhD, Statistics, 2011, Virginia Tech

 The focus of this work is the development of testing procedures for the existence of change-points in parametric hazard models of various types. Hazard functions… (more)

Subjects/Keywords: Gaussian process; Donsker class; Change-point; hazard function; local asymptotic normality; Likelihood ratio test

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APA (6th Edition):

Williams, M. R. (2011). Likelihood-based testing and model selection for hazard functions with unknown change-points. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/26835

Chicago Manual of Style (16th Edition):

Williams, Matthew Richard. “Likelihood-based testing and model selection for hazard functions with unknown change-points.” 2011. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/26835.

MLA Handbook (7th Edition):

Williams, Matthew Richard. “Likelihood-based testing and model selection for hazard functions with unknown change-points.” 2011. Web. 19 Oct 2019.

Vancouver:

Williams MR. Likelihood-based testing and model selection for hazard functions with unknown change-points. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/26835.

Council of Science Editors:

Williams MR. Likelihood-based testing and model selection for hazard functions with unknown change-points. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/26835


Virginia Tech

12. Mahmoud, Hamdy Fayez Farahat. Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data.

Degree: PhD, Statistics, 2014, Virginia Tech

 Semiparametric modeling is a hybrid of the parametric and nonparametric modelings where some function forms are known and others are unknown. In this dissertation, we… (more)

Subjects/Keywords: Change Point; Generalized Linear Model; Generalized Additive Model; Markov Chain Expectation Maximization; Mixed model; Permutation Test; Semiparametric regression; Single Index model; Spatially correlated data; Spatio-temporal data.

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APA (6th Edition):

Mahmoud, H. F. F. (2014). Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/76744

Chicago Manual of Style (16th Edition):

Mahmoud, Hamdy Fayez Farahat. “Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data.” 2014. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/76744.

MLA Handbook (7th Edition):

Mahmoud, Hamdy Fayez Farahat. “Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data.” 2014. Web. 19 Oct 2019.

Vancouver:

Mahmoud HFF. Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/76744.

Council of Science Editors:

Mahmoud HFF. Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/76744


Virginia Tech

13. Szarka III, John Louis. Surveillance of Negative Binomial and Bernoulli Processes.

Degree: PhD, Statistics, 2011, Virginia Tech

 The evaluation of discrete processes are performed for industrial and healthcare processes. Count data may be used to measure the number of defective items in… (more)

Subjects/Keywords: Adaptive threshold; High quality processes; Statistical process control; CUSUM charts; Biosurveillance; W2 method; UGR chart; Attributes data

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APA (6th Edition):

Szarka III, J. L. (2011). Surveillance of Negative Binomial and Bernoulli Processes. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/26617

Chicago Manual of Style (16th Edition):

Szarka III, John Louis. “Surveillance of Negative Binomial and Bernoulli Processes.” 2011. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/26617.

MLA Handbook (7th Edition):

Szarka III, John Louis. “Surveillance of Negative Binomial and Bernoulli Processes.” 2011. Web. 19 Oct 2019.

Vancouver:

Szarka III JL. Surveillance of Negative Binomial and Bernoulli Processes. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/26617.

Council of Science Editors:

Szarka III JL. Surveillance of Negative Binomial and Bernoulli Processes. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/26617


Virginia Tech

14. Fang, Zaili. Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data.

Degree: PhD, Statistics, 2012, Virginia Tech

 Model and variable selection have attracted considerable attention in areas of application where datasets usually contain thousands of variables. Variable selection is a critical step… (more)

Subjects/Keywords: Variable Selection; Smoothing Splines; Sparsistency; Semiparametric Model; Pathway Analysis; Additive Model; Cluster Algorithm; Gaussian Random Process; Global-Local Shrinkage; Graphical Model; Ising Model; Kernel Machine; KM Model; LASSO; Long Tail Prior; Mixture Normals; Model Selection; Multivariate Smoothing Function; Nonnegative Garrote; Nonparametric Model

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APA (6th Edition):

Fang, Z. (2012). Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/40090

Chicago Manual of Style (16th Edition):

Fang, Zaili. “Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data.” 2012. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/40090.

MLA Handbook (7th Edition):

Fang, Zaili. “Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data.” 2012. Web. 19 Oct 2019.

Vancouver:

Fang Z. Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/40090.

Council of Science Editors:

Fang Z. Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/40090


Virginia Tech

15. Cheng, Lulu. Statistical Methods for Genetic Pathway-Based Data Analysis.

Degree: PhD, Statistics, 2013, Virginia Tech

 The wide application of the genomic microarray technology triggers a tremendous need in the development of the high dimensional genetic data analysis. Many statistical methods… (more)

Subjects/Keywords: Adaptive GLASSO; Gaussian Random Process; Gene Expression Data; GLASSO; Marginal Likelihood; Multi-Level Gaussian Graphical Model; Pathway-Based Analysis; Unknown Link Estimation; Zero Inflated Poisson.

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APA (6th Edition):

Cheng, L. (2013). Statistical Methods for Genetic Pathway-Based Data Analysis. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/52039

Chicago Manual of Style (16th Edition):

Cheng, Lulu. “Statistical Methods for Genetic Pathway-Based Data Analysis.” 2013. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/52039.

MLA Handbook (7th Edition):

Cheng, Lulu. “Statistical Methods for Genetic Pathway-Based Data Analysis.” 2013. Web. 19 Oct 2019.

Vancouver:

Cheng L. Statistical Methods for Genetic Pathway-Based Data Analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/52039.

Council of Science Editors:

Cheng L. Statistical Methods for Genetic Pathway-Based Data Analysis. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/52039


Virginia Tech

16. Zhang, Huaiye. Bayesian Approach Dealing with Mixture Model Problems.

Degree: PhD, Statistics, 2012, Virginia Tech

 In this dissertation, we focus on two research topics related to mixture models. The first topic is Adaptive Rejection Metropolis Simulated Annealing for Detecting Global… (more)

Subjects/Keywords: Infinite Mixture Model; Hierarchical Model; Nonlinear Mixed Effects Model; Dirichlet Process; Simulated Annealing; Adaptive Rejection Metropolis Sampling

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APA (6th Edition):

Zhang, H. (2012). Bayesian Approach Dealing with Mixture Model Problems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/37681

Chicago Manual of Style (16th Edition):

Zhang, Huaiye. “Bayesian Approach Dealing with Mixture Model Problems.” 2012. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/37681.

MLA Handbook (7th Edition):

Zhang, Huaiye. “Bayesian Approach Dealing with Mixture Model Problems.” 2012. Web. 19 Oct 2019.

Vancouver:

Zhang H. Bayesian Approach Dealing with Mixture Model Problems. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/37681.

Council of Science Editors:

Zhang H. Bayesian Approach Dealing with Mixture Model Problems. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/37681


Virginia Tech

17. Roberts, Lucas R. Variable Selection and Decision Trees: The DiVaS and ALoVaS Methods.

Degree: PhD, Statistics, 2014, Virginia Tech

 In this thesis we propose a novel modification to Bayesian decision tree methods. We provide a historical survey of the statistics and computer science research… (more)

Subjects/Keywords: Statistics; Decision Trees; Variable selection; Additive Logistic Normal

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APA (6th Edition):

Roberts, L. R. (2014). Variable Selection and Decision Trees: The DiVaS and ALoVaS Methods. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/70878

Chicago Manual of Style (16th Edition):

Roberts, Lucas R. “Variable Selection and Decision Trees: The DiVaS and ALoVaS Methods.” 2014. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/70878.

MLA Handbook (7th Edition):

Roberts, Lucas R. “Variable Selection and Decision Trees: The DiVaS and ALoVaS Methods.” 2014. Web. 19 Oct 2019.

Vancouver:

Roberts LR. Variable Selection and Decision Trees: The DiVaS and ALoVaS Methods. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/70878.

Council of Science Editors:

Roberts LR. Variable Selection and Decision Trees: The DiVaS and ALoVaS Methods. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/70878


Virginia Tech

18. Slifko, Matthew D. The Cauchy-Net Mixture Model for Clustering with Anomalous Data.

Degree: PhD, Statistics, 2019, Virginia Tech

 We live in the data explosion era. The unprecedented amount of data offers a potential wealth of knowledge but also brings about concerns regarding ethical… (more)

Subjects/Keywords: Bayesian Nonparametrics; Dirichlet Process Mixture Model; Clustering; Anomaly Detection

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APA (6th Edition):

Slifko, M. D. (2019). The Cauchy-Net Mixture Model for Clustering with Anomalous Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/93576

Chicago Manual of Style (16th Edition):

Slifko, Matthew D. “The Cauchy-Net Mixture Model for Clustering with Anomalous Data.” 2019. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/93576.

MLA Handbook (7th Edition):

Slifko, Matthew D. “The Cauchy-Net Mixture Model for Clustering with Anomalous Data.” 2019. Web. 19 Oct 2019.

Vancouver:

Slifko MD. The Cauchy-Net Mixture Model for Clustering with Anomalous Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/93576.

Council of Science Editors:

Slifko MD. The Cauchy-Net Mixture Model for Clustering with Anomalous Data. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/93576

19. Li, Han. Statistical Modeling and Analysis of Bivariate Spatial-Temporal Data with the Application to Stream Temperature Study.

Degree: PhD, Statistics, 2014, Virginia Tech

 Water temperature is a critical factor for the quality and biological condition of streams. Among various factors affecting stream water temperature, air temperature is one… (more)

Subjects/Keywords: Steam Temperature; Varying Coefficient Model; Functional Data Clustering; Missing Data Imputation

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APA (6th Edition):

Li, H. (2014). Statistical Modeling and Analysis of Bivariate Spatial-Temporal Data with the Application to Stream Temperature Study. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/70862

Chicago Manual of Style (16th Edition):

Li, Han. “Statistical Modeling and Analysis of Bivariate Spatial-Temporal Data with the Application to Stream Temperature Study.” 2014. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/70862.

MLA Handbook (7th Edition):

Li, Han. “Statistical Modeling and Analysis of Bivariate Spatial-Temporal Data with the Application to Stream Temperature Study.” 2014. Web. 19 Oct 2019.

Vancouver:

Li H. Statistical Modeling and Analysis of Bivariate Spatial-Temporal Data with the Application to Stream Temperature Study. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/70862.

Council of Science Editors:

Li H. Statistical Modeling and Analysis of Bivariate Spatial-Temporal Data with the Application to Stream Temperature Study. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/70862


Virginia Tech

20. Chen, Jinsong. Semiparametric Methods for the Generalized Linear Model.

Degree: PhD, Statistics, 2010, Virginia Tech

 The generalized linear model (GLM) is a popular model in many research areas. In the GLM, each outcome of the dependent variable is assumed to… (more)

Subjects/Keywords: Penalized splines; Generalized linear mixed model; Generalized linear model; Single-Index Model

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APA (6th Edition):

Chen, J. (2010). Semiparametric Methods for the Generalized Linear Model. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28012

Chicago Manual of Style (16th Edition):

Chen, Jinsong. “Semiparametric Methods for the Generalized Linear Model.” 2010. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/28012.

MLA Handbook (7th Edition):

Chen, Jinsong. “Semiparametric Methods for the Generalized Linear Model.” 2010. Web. 19 Oct 2019.

Vancouver:

Chen J. Semiparametric Methods for the Generalized Linear Model. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/28012.

Council of Science Editors:

Chen J. Semiparametric Methods for the Generalized Linear Model. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/28012


Virginia Tech

21. Maiti, Dipayan. Multiset Model Selection and Averaging, and Interactive Storytelling.

Degree: PhD, Statistics, 2012, Virginia Tech

 The Multiset Sampler [Leman et al., 2009] has previously been deployed and developed for efficient sampling from complex stochastic processes. We extend the sampler and… (more)

Subjects/Keywords: supervised topic modeling; visual analytics; bayesian model averaging; Bayesian mode selection

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APA (6th Edition):

Maiti, D. (2012). Multiset Model Selection and Averaging, and Interactive Storytelling. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28563

Chicago Manual of Style (16th Edition):

Maiti, Dipayan. “Multiset Model Selection and Averaging, and Interactive Storytelling.” 2012. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/28563.

MLA Handbook (7th Edition):

Maiti, Dipayan. “Multiset Model Selection and Averaging, and Interactive Storytelling.” 2012. Web. 19 Oct 2019.

Vancouver:

Maiti D. Multiset Model Selection and Averaging, and Interactive Storytelling. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/28563.

Council of Science Editors:

Maiti D. Multiset Model Selection and Averaging, and Interactive Storytelling. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/28563


Virginia Tech

22. Mishra, Anurag. Estimating Uncertainty in HSPF based Water Quality Model: Application of Monte-Carlo Based Techniques.

Degree: PhD, Biological Systems Engineering, 2011, Virginia Tech

 To propose a methodology for the uncertainty estimation in water quality modeling as related to TMDL development, four Monte Carlo (MC) based techniquesâ single-phase MC,… (more)

Subjects/Keywords: water quality modeling; TMDL; fecal coliform; HSPF; uncertainty analysis; Monte-Carlo; Bayesian techniques; GLUE; MCMC; two-phase Monte Carlo analysis

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APA (6th Edition):

Mishra, A. (2011). Estimating Uncertainty in HSPF based Water Quality Model: Application of Monte-Carlo Based Techniques. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28777

Chicago Manual of Style (16th Edition):

Mishra, Anurag. “Estimating Uncertainty in HSPF based Water Quality Model: Application of Monte-Carlo Based Techniques.” 2011. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/28777.

MLA Handbook (7th Edition):

Mishra, Anurag. “Estimating Uncertainty in HSPF based Water Quality Model: Application of Monte-Carlo Based Techniques.” 2011. Web. 19 Oct 2019.

Vancouver:

Mishra A. Estimating Uncertainty in HSPF based Water Quality Model: Application of Monte-Carlo Based Techniques. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/28777.

Council of Science Editors:

Mishra A. Estimating Uncertainty in HSPF based Water Quality Model: Application of Monte-Carlo Based Techniques. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/28777

23. Crandell, Ian C. Semi-Supervised Anomaly Detection and Heterogeneous Covariance Estimation for Gaussian Processes.

Degree: PhD, Statistics, 2017, Virginia Tech

 In this thesis, we propose a statistical framework for estimating correlation between sensor systems measuring diverse physical phenomenon. We consider systems that measure at different… (more)

Subjects/Keywords: Gaussian processes; heterogeneity; aeroacoustics; semi-supervised learning

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APA (6th Edition):

Crandell, I. C. (2017). Semi-Supervised Anomaly Detection and Heterogeneous Covariance Estimation for Gaussian Processes. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81187

Chicago Manual of Style (16th Edition):

Crandell, Ian C. “Semi-Supervised Anomaly Detection and Heterogeneous Covariance Estimation for Gaussian Processes.” 2017. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/81187.

MLA Handbook (7th Edition):

Crandell, Ian C. “Semi-Supervised Anomaly Detection and Heterogeneous Covariance Estimation for Gaussian Processes.” 2017. Web. 19 Oct 2019.

Vancouver:

Crandell IC. Semi-Supervised Anomaly Detection and Heterogeneous Covariance Estimation for Gaussian Processes. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/81187.

Council of Science Editors:

Crandell IC. Semi-Supervised Anomaly Detection and Heterogeneous Covariance Estimation for Gaussian Processes. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/81187

24. Hu, Xinran. On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm.

Degree: PhD, Statistics, 2015, Virginia Tech

 Big Data is transforming the way we live. From medical care to social networks, data is playing a central role in various applications. As the… (more)

Subjects/Keywords: Visual Analytics; Big Data Monte Carlo Sampling

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APA (6th Edition):

Hu, X. (2015). On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51224

Chicago Manual of Style (16th Edition):

Hu, Xinran. “On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm.” 2015. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/51224.

MLA Handbook (7th Edition):

Hu, Xinran. “On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm.” 2015. Web. 19 Oct 2019.

Vancouver:

Hu X. On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/51224.

Council of Science Editors:

Hu X. On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/51224

25. Hatch, Joshua M. The Effects of Ageing Error on Stock Assessment for Weakfish Cynoscion regalis.

Degree: MS, Fisheries and Wildlife Sciences, 2013, Virginia Tech

 Inherent uncertainties in the stock assessment for weakfish have precluded accurate and consistent advice concerning the management of commercial and recreational fisheries. Error within ageing… (more)

Subjects/Keywords: Ageing error; Weakfish; Bayesian; Statistical catch-at-age; Simulation

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APA (6th Edition):

Hatch, J. M. (2013). The Effects of Ageing Error on Stock Assessment for Weakfish Cynoscion regalis. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/50988

Chicago Manual of Style (16th Edition):

Hatch, Joshua M. “The Effects of Ageing Error on Stock Assessment for Weakfish Cynoscion regalis.” 2013. Masters Thesis, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/50988.

MLA Handbook (7th Edition):

Hatch, Joshua M. “The Effects of Ageing Error on Stock Assessment for Weakfish Cynoscion regalis.” 2013. Web. 19 Oct 2019.

Vancouver:

Hatch JM. The Effects of Ageing Error on Stock Assessment for Weakfish Cynoscion regalis. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/50988.

Council of Science Editors:

Hatch JM. The Effects of Ageing Error on Stock Assessment for Weakfish Cynoscion regalis. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/50988


Virginia Tech

26. Li, Zhonggai. Objective Bayesian Analysis of Kullback-Liebler Divergence of two Multivariate Normal Distributions with Common Covariance Matrix and Star-shape Gaussian Graphical Model.

Degree: PhD, Statistics, 2008, Virginia Tech

 This dissertation consists of four independent but related parts, each in a Chapter. The first part is an introductory. It serves as the background introduction… (more)

Subjects/Keywords: Multivariate Normal Distributions; Monte Carlo; Star-shape Gaussian Graphical Model; Objective Priors; Jeffreys' Priors; Reference Priors; Invariant Haar Prior; Fisher Information Matrix; Frequentist Matching; Kullback-Liebler Divergence

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APA (6th Edition):

Li, Z. (2008). Objective Bayesian Analysis of Kullback-Liebler Divergence of two Multivariate Normal Distributions with Common Covariance Matrix and Star-shape Gaussian Graphical Model. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28121

Chicago Manual of Style (16th Edition):

Li, Zhonggai. “Objective Bayesian Analysis of Kullback-Liebler Divergence of two Multivariate Normal Distributions with Common Covariance Matrix and Star-shape Gaussian Graphical Model.” 2008. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/28121.

MLA Handbook (7th Edition):

Li, Zhonggai. “Objective Bayesian Analysis of Kullback-Liebler Divergence of two Multivariate Normal Distributions with Common Covariance Matrix and Star-shape Gaussian Graphical Model.” 2008. Web. 19 Oct 2019.

Vancouver:

Li Z. Objective Bayesian Analysis of Kullback-Liebler Divergence of two Multivariate Normal Distributions with Common Covariance Matrix and Star-shape Gaussian Graphical Model. [Internet] [Doctoral dissertation]. Virginia Tech; 2008. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/28121.

Council of Science Editors:

Li Z. Objective Bayesian Analysis of Kullback-Liebler Divergence of two Multivariate Normal Distributions with Common Covariance Matrix and Star-shape Gaussian Graphical Model. [Doctoral Dissertation]. Virginia Tech; 2008. Available from: http://hdl.handle.net/10919/28121


Virginia Tech

27. Willey, Katherine Tara. Environmental Factors Determining the Pre-Restoration Benthic Macroinvertebrate Assemblage In A Stream Used By Cattle.

Degree: MS, Entomology, 2008, Virginia Tech

 I investigated the baseline benthic macroinvertebrate community in relation to the environmental conditions in a section of Smith Creek, north of Harrisonburg, VA, prior to… (more)

Subjects/Keywords: nutrients; sediment; macroinvertebrates; cattle grazing; recovery; restoration; aquatic ecology

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APA (6th Edition):

Willey, K. T. (2008). Environmental Factors Determining the Pre-Restoration Benthic Macroinvertebrate Assemblage In A Stream Used By Cattle. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/35221

Chicago Manual of Style (16th Edition):

Willey, Katherine Tara. “Environmental Factors Determining the Pre-Restoration Benthic Macroinvertebrate Assemblage In A Stream Used By Cattle.” 2008. Masters Thesis, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/35221.

MLA Handbook (7th Edition):

Willey, Katherine Tara. “Environmental Factors Determining the Pre-Restoration Benthic Macroinvertebrate Assemblage In A Stream Used By Cattle.” 2008. Web. 19 Oct 2019.

Vancouver:

Willey KT. Environmental Factors Determining the Pre-Restoration Benthic Macroinvertebrate Assemblage In A Stream Used By Cattle. [Internet] [Masters thesis]. Virginia Tech; 2008. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/35221.

Council of Science Editors:

Willey KT. Environmental Factors Determining the Pre-Restoration Benthic Macroinvertebrate Assemblage In A Stream Used By Cattle. [Masters Thesis]. Virginia Tech; 2008. Available from: http://hdl.handle.net/10919/35221


Virginia Tech

28. McGraw, John M. An Investigation into Classification of High Dimensional Frequency Data.

Degree: MS, Statistics, 2001, Virginia Tech

 We desire an algorithm to classify a physical object in ``real-time" using an easily portable probing device. The probe excites a given object at frequencies… (more)

Subjects/Keywords: Multivariate Normal; Frequency Response; Confidence Interval; Data Analysis; Correlation; Maximum Likelihood

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APA (6th Edition):

McGraw, J. M. (2001). An Investigation into Classification of High Dimensional Frequency Data. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/35487

Chicago Manual of Style (16th Edition):

McGraw, John M. “An Investigation into Classification of High Dimensional Frequency Data.” 2001. Masters Thesis, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/35487.

MLA Handbook (7th Edition):

McGraw, John M. “An Investigation into Classification of High Dimensional Frequency Data.” 2001. Web. 19 Oct 2019.

Vancouver:

McGraw JM. An Investigation into Classification of High Dimensional Frequency Data. [Internet] [Masters thesis]. Virginia Tech; 2001. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/35487.

Council of Science Editors:

McGraw JM. An Investigation into Classification of High Dimensional Frequency Data. [Masters Thesis]. Virginia Tech; 2001. Available from: http://hdl.handle.net/10919/35487


Virginia Tech

29. Arnegard, Matthew E. Toxicant-releasing substrates :a new method for delivering copper to microbial communities in SITU.

Degree: MS, Biology, 1993, Virginia Tech

  Currently, protocols for investigating the effects of chemical pollutants on periphyton communities under natural conditions are statistically flawed and/or potentially harmful to the ecosystems… (more)

Subjects/Keywords: Copper; LD5655.V855 1993.A764

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APA (6th Edition):

Arnegard, M. E. (1993). Toxicant-releasing substrates :a new method for delivering copper to microbial communities in SITU. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/46238

Chicago Manual of Style (16th Edition):

Arnegard, Matthew E. “Toxicant-releasing substrates :a new method for delivering copper to microbial communities in SITU.” 1993. Masters Thesis, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/46238.

MLA Handbook (7th Edition):

Arnegard, Matthew E. “Toxicant-releasing substrates :a new method for delivering copper to microbial communities in SITU.” 1993. Web. 19 Oct 2019.

Vancouver:

Arnegard ME. Toxicant-releasing substrates :a new method for delivering copper to microbial communities in SITU. [Internet] [Masters thesis]. Virginia Tech; 1993. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/46238.

Council of Science Editors:

Arnegard ME. Toxicant-releasing substrates :a new method for delivering copper to microbial communities in SITU. [Masters Thesis]. Virginia Tech; 1993. Available from: http://hdl.handle.net/10919/46238


Virginia Tech

30. Lee, Mi Hyun. On Independent Reference Priors.

Degree: PhD, Statistics, 2007, Virginia Tech

 In Bayesian inference, the choice of prior has been of great interest. Subjective priors are ideal if sufficient information on priors is available. However, in… (more)

Subjects/Keywords: Independent reference priors; Reference priors; Probability matching priors

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APA (6th Edition):

Lee, M. H. (2007). On Independent Reference Priors. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/30096

Chicago Manual of Style (16th Edition):

Lee, Mi Hyun. “On Independent Reference Priors.” 2007. Doctoral Dissertation, Virginia Tech. Accessed October 19, 2019. http://hdl.handle.net/10919/30096.

MLA Handbook (7th Edition):

Lee, Mi Hyun. “On Independent Reference Priors.” 2007. Web. 19 Oct 2019.

Vancouver:

Lee MH. On Independent Reference Priors. [Internet] [Doctoral dissertation]. Virginia Tech; 2007. [cited 2019 Oct 19]. Available from: http://hdl.handle.net/10919/30096.

Council of Science Editors:

Lee MH. On Independent Reference Priors. [Doctoral Dissertation]. Virginia Tech; 2007. Available from: http://hdl.handle.net/10919/30096

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