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You searched for +publisher:"Virginia Tech" +contributor:("House, Leanna L."). Showing records 1 – 28 of 28 total matches.

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1. Yu, Ling. Three Essays in Applied Microeconomics.

Degree: PhD, Economics, Agriculture and Life Sciences, 2017, Virginia Tech

 This dissertation consists of three research papers in Applied Microeconomics. Each paper uses an econometric technique to analyze a problem related to human behavior. The… (more)

Subjects/Keywords: Applied Microeconomics; Applied Econometrics; Human Behavior

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APA (6th Edition):

Yu, L. (2017). Three Essays in Applied Microeconomics. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78860

Chicago Manual of Style (16th Edition):

Yu, Ling. “Three Essays in Applied Microeconomics.” 2017. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/78860.

MLA Handbook (7th Edition):

Yu, Ling. “Three Essays in Applied Microeconomics.” 2017. Web. 07 Apr 2020.

Vancouver:

Yu L. Three Essays in Applied Microeconomics. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/78860.

Council of Science Editors:

Yu L. Three Essays in Applied Microeconomics. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/78860

2. Zhang, Lin. Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data.

Degree: PhD, Statistics, 2018, Virginia Tech

 We are living in an era in which many mysteries related to science, technologies and design can be answered by "learning" the huge amount of… (more)

Subjects/Keywords: Gaussian Process; Kernel Machine; Mixture Model; Pathway-Based Analysis; Semiparametric Bayesian Hierarchical Survival Model

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APA (6th Edition):

Zhang, L. (2018). Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/95040

Chicago Manual of Style (16th Edition):

Zhang, Lin. “Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data.” 2018. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/95040.

MLA Handbook (7th Edition):

Zhang, Lin. “Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data.” 2018. Web. 07 Apr 2020.

Vancouver:

Zhang L. Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/95040.

Council of Science Editors:

Zhang L. Semiparametric Bayesian Kernel Survival Model for Highly Correlated High-Dimensional Data. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/95040


Virginia Tech

3. Chen, Xin. Be the Data: Embodied Visual Analytics.

Degree: MS, Computer Science, 2016, Virginia Tech

 With the rise of big data, it is becoming increasingly important to educate students about data analytics. In particular, students without a strong mathematical background… (more)

Subjects/Keywords: Visual Analytics; Embodied Interaction; Collaborative Learning; Human-Computer Interaction; Immersive Environment

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APA (6th Edition):

Chen, X. (2016). Be the Data: Embodied Visual Analytics. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/72287

Chicago Manual of Style (16th Edition):

Chen, Xin. “Be the Data: Embodied Visual Analytics.” 2016. Masters Thesis, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/72287.

MLA Handbook (7th Edition):

Chen, Xin. “Be the Data: Embodied Visual Analytics.” 2016. Web. 07 Apr 2020.

Vancouver:

Chen X. Be the Data: Embodied Visual Analytics. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/72287.

Council of Science Editors:

Chen X. Be the Data: Embodied Visual Analytics. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/72287


Virginia Tech

4. Whiting, Nolan Wagner. Assessment of Model Validation, Calibration, and Prediction Approaches in the Presence of Uncertainty.

Degree: MS, Aerospace Engineering, 2019, Virginia Tech

 Uncertainties often exists when conducting physical experiments, and whether this uncertainty exists due to input uncertainty, uncertainty in the environmental conditions in which the experiment… (more)

Subjects/Keywords: Validation; Calibration; Prediction; Uncertainty Quantification

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APA (6th Edition):

Whiting, N. W. (2019). Assessment of Model Validation, Calibration, and Prediction Approaches in the Presence of Uncertainty. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/91903

Chicago Manual of Style (16th Edition):

Whiting, Nolan Wagner. “Assessment of Model Validation, Calibration, and Prediction Approaches in the Presence of Uncertainty.” 2019. Masters Thesis, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/91903.

MLA Handbook (7th Edition):

Whiting, Nolan Wagner. “Assessment of Model Validation, Calibration, and Prediction Approaches in the Presence of Uncertainty.” 2019. Web. 07 Apr 2020.

Vancouver:

Whiting NW. Assessment of Model Validation, Calibration, and Prediction Approaches in the Presence of Uncertainty. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/91903.

Council of Science Editors:

Whiting NW. Assessment of Model Validation, Calibration, and Prediction Approaches in the Presence of Uncertainty. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/91903


Virginia Tech

5. Porter, Erica May. Applying an Intrinsic Conditional Autoregressive Reference Prior for Areal Data.

Degree: MS, Statistics, 2019, Virginia Tech

 Spatial data is increasingly relevant in a wide variety of research areas. Economists, medical researchers, ecologists, and policymakers all make critical decisions about populations using… (more)

Subjects/Keywords: Bayesian Analysis; Spatial Statistics

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APA (6th Edition):

Porter, E. M. (2019). Applying an Intrinsic Conditional Autoregressive Reference Prior for Areal Data. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/91385

Chicago Manual of Style (16th Edition):

Porter, Erica May. “Applying an Intrinsic Conditional Autoregressive Reference Prior for Areal Data.” 2019. Masters Thesis, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/91385.

MLA Handbook (7th Edition):

Porter, Erica May. “Applying an Intrinsic Conditional Autoregressive Reference Prior for Areal Data.” 2019. Web. 07 Apr 2020.

Vancouver:

Porter EM. Applying an Intrinsic Conditional Autoregressive Reference Prior for Areal Data. [Internet] [Masters thesis]. Virginia Tech; 2019. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/91385.

Council of Science Editors:

Porter EM. Applying an Intrinsic Conditional Autoregressive Reference Prior for Areal Data. [Masters Thesis]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/91385


Virginia Tech

6. Xu, Yangyi. Frequentist-Bayesian Hybrid Tests in Semi-parametric and Non-parametric Models with Low/High-Dimensional Covariate.

Degree: PhD, Statistics, 2014, Virginia Tech

 We provide a Frequentist-Bayesian hybrid test statistic in this dissertation for two testing problems. The first one is to design a test for the significant… (more)

Subjects/Keywords: Bayes Factor; Bayes Sum Test; Discrete Fourier Transform; Hybrid; Laplace approximation; Neyman Test; Omnibus; Resampling; Score; Single index; Spline Approximation

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APA (6th Edition):

Xu, Y. (2014). Frequentist-Bayesian Hybrid Tests in Semi-parametric and Non-parametric Models with Low/High-Dimensional Covariate. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71285

Chicago Manual of Style (16th Edition):

Xu, Yangyi. “Frequentist-Bayesian Hybrid Tests in Semi-parametric and Non-parametric Models with Low/High-Dimensional Covariate.” 2014. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/71285.

MLA Handbook (7th Edition):

Xu, Yangyi. “Frequentist-Bayesian Hybrid Tests in Semi-parametric and Non-parametric Models with Low/High-Dimensional Covariate.” 2014. Web. 07 Apr 2020.

Vancouver:

Xu Y. Frequentist-Bayesian Hybrid Tests in Semi-parametric and Non-parametric Models with Low/High-Dimensional Covariate. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/71285.

Council of Science Editors:

Xu Y. Frequentist-Bayesian Hybrid Tests in Semi-parametric and Non-parametric Models with Low/High-Dimensional Covariate. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/71285

7. 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 April 07, 2020. 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. 07 Apr 2020.

Vancouver:

Crandell IC. Semi-Supervised Anomaly Detection and Heterogeneous Covariance Estimation for Gaussian Processes. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2020 Apr 07]. 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

8. Fang, Youjia. Modeling Driving Risk Using Naturalistic Driving Study Data.

Degree: PhD, Statistics, 2014, Virginia Tech

 Motor vehicle crashes are one of the leading causes of death in the United States. Traffic safety research targets at understanding the cause of crash,… (more)

Subjects/Keywords: Naturalistic Driving Study; Driving Risk; Poisson Regression; Bayesian Model; Random Exposure; Hierarchical Model; Meta-Analysis

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APA (6th Edition):

Fang, Y. (2014). Modeling Driving Risk Using Naturalistic Driving Study Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/65151

Chicago Manual of Style (16th Edition):

Fang, Youjia. “Modeling Driving Risk Using Naturalistic Driving Study Data.” 2014. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/65151.

MLA Handbook (7th Edition):

Fang, Youjia. “Modeling Driving Risk Using Naturalistic Driving Study Data.” 2014. Web. 07 Apr 2020.

Vancouver:

Fang Y. Modeling Driving Risk Using Naturalistic Driving Study Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/65151.

Council of Science Editors:

Fang Y. Modeling Driving Risk Using Naturalistic Driving Study Data. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/65151

9. 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 April 07, 2020. 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. 07 Apr 2020.

Vancouver:

Hu X. On Grouped Observation Level Interaction and a Big Data Monte Carlo Sampling Algorithm. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2020 Apr 07]. 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

10. Huang, Jiangeng. Sequential learning, large-scale calibration, and uncertainty quantification.

Degree: PhD, Statistics, 2019, Virginia Tech

 With remarkable advances in computing power, complex physical systems today can be simulated comparatively cheaply and to high accuracy through computer experiments. Computer experiments continue… (more)

Subjects/Keywords: sequential learning; computer experiments; uncertainty quantification; big data; hierarchical modeling

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APA (6th Edition):

Huang, J. (2019). Sequential learning, large-scale calibration, and uncertainty quantification. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/91935

Chicago Manual of Style (16th Edition):

Huang, Jiangeng. “Sequential learning, large-scale calibration, and uncertainty quantification.” 2019. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/91935.

MLA Handbook (7th Edition):

Huang, Jiangeng. “Sequential learning, large-scale calibration, and uncertainty quantification.” 2019. Web. 07 Apr 2020.

Vancouver:

Huang J. Sequential learning, large-scale calibration, and uncertainty quantification. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/91935.

Council of Science Editors:

Huang J. Sequential learning, large-scale calibration, and uncertainty quantification. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/91935


Virginia Tech

11. Saraf, Parang. A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction.

Degree: PhD, Computer Science, 2018, Virginia Tech

 Automated event extraction from free text remains an open problem, particularly when the goal is to identify all relevant events. Manual extraction is currently the… (more)

Subjects/Keywords: Event Extraction; Visual Analytics; News Analytics; Civil Unrest

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APA (6th Edition):

Saraf, P. (2018). A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82926

Chicago Manual of Style (16th Edition):

Saraf, Parang. “A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction.” 2018. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/82926.

MLA Handbook (7th Edition):

Saraf, Parang. “A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction.” 2018. Web. 07 Apr 2020.

Vancouver:

Saraf P. A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/82926.

Council of Science Editors:

Saraf P. A Cost-Effective Semi-Automated Approach for Comprehensive Event Extraction. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/82926


Virginia Tech

12. Shropshire, Kevin O'Neil. Impact of Ignoring Nested Data Structures on Ability Estimation.

Degree: PhD, Educational Leadership and Policy Studies, 2014, Virginia Tech

 The literature is clear that intentional or unintentional clustering of data elements typically results in the inflation of the estimated standard error of fixed parameter… (more)

Subjects/Keywords: Complex survey designs; clustering; PSU; nested data; multilevel data; hierarchical data; two-level HGLM; three-level HGLM; Rasch; ability estimation

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APA (6th Edition):

Shropshire, K. O. (2014). Impact of Ignoring Nested Data Structures on Ability Estimation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64197

Chicago Manual of Style (16th Edition):

Shropshire, Kevin O'Neil. “Impact of Ignoring Nested Data Structures on Ability Estimation.” 2014. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/64197.

MLA Handbook (7th Edition):

Shropshire, Kevin O'Neil. “Impact of Ignoring Nested Data Structures on Ability Estimation.” 2014. Web. 07 Apr 2020.

Vancouver:

Shropshire KO. Impact of Ignoring Nested Data Structures on Ability Estimation. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/64197.

Council of Science Editors:

Shropshire KO. Impact of Ignoring Nested Data Structures on Ability Estimation. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64197


Virginia Tech

13. Loftus, Stephen Christopher. On the Use of Grouped Covariate Regression in Oversaturated Models.

Degree: PhD, Statistics, 2015, Virginia Tech

 As data collection techniques improve, oftentimes the number of covariates exceeds the number of observations. When this happens, regression models become oversaturated and, thus, inestimable.… (more)

Subjects/Keywords: Oversaturated model; Big data; Variable selection; Data Analytics; Bayesian methods

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APA (6th Edition):

Loftus, S. C. (2015). On the Use of Grouped Covariate Regression in Oversaturated Models. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64363

Chicago Manual of Style (16th Edition):

Loftus, Stephen Christopher. “On the Use of Grouped Covariate Regression in Oversaturated Models.” 2015. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/64363.

MLA Handbook (7th Edition):

Loftus, Stephen Christopher. “On the Use of Grouped Covariate Regression in Oversaturated Models.” 2015. Web. 07 Apr 2020.

Vancouver:

Loftus SC. On the Use of Grouped Covariate Regression in Oversaturated Models. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/64363.

Council of Science Editors:

Loftus SC. On the Use of Grouped Covariate Regression in Oversaturated Models. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/64363


Virginia Tech

14. 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 April 07, 2020. http://hdl.handle.net/10919/27791.

MLA Handbook (7th Edition):

Velasco-Cruz, Ciro. “Spatially Correlated Model Selection (SCOMS).” 2012. Web. 07 Apr 2020.

Vancouver:

Velasco-Cruz C. Spatially Correlated Model Selection (SCOMS). [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2020 Apr 07]. 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

15. 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 April 07, 2020. http://hdl.handle.net/10919/19210.

MLA Handbook (7th Edition):

Han, Chao. “Bayesian Visual Analytics: Interactive Visualization for High Dimensional Data.” 2012. Web. 07 Apr 2020.

Vancouver:

Han C. Bayesian Visual Analytics: Interactive Visualization for High Dimensional Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2020 Apr 07]. 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

16. Carzolio, Marcos Arantes. On a Selection of Advanced Markov Chain Monte Carlo Algorithms for Everyday Use: Weighted Particle Tempering, Practical Reversible Jump, and Extensions.

Degree: PhD, Statistics, 2016, Virginia Tech

 We are entering an exciting era, rich in the availability of data via sources such as the Internet, satellites, particle colliders, telecommunication networks, computer simulations,… (more)

Subjects/Keywords: Markov chain Monte Carlo; reversible jump; weighted particle tempering

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APA (6th Edition):

Carzolio, M. A. (2016). On a Selection of Advanced Markov Chain Monte Carlo Algorithms for Everyday Use: Weighted Particle Tempering, Practical Reversible Jump, and Extensions. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71765

Chicago Manual of Style (16th Edition):

Carzolio, Marcos Arantes. “On a Selection of Advanced Markov Chain Monte Carlo Algorithms for Everyday Use: Weighted Particle Tempering, Practical Reversible Jump, and Extensions.” 2016. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/71765.

MLA Handbook (7th Edition):

Carzolio, Marcos Arantes. “On a Selection of Advanced Markov Chain Monte Carlo Algorithms for Everyday Use: Weighted Particle Tempering, Practical Reversible Jump, and Extensions.” 2016. Web. 07 Apr 2020.

Vancouver:

Carzolio MA. On a Selection of Advanced Markov Chain Monte Carlo Algorithms for Everyday Use: Weighted Particle Tempering, Practical Reversible Jump, and Extensions. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/71765.

Council of Science Editors:

Carzolio MA. On a Selection of Advanced Markov Chain Monte Carlo Algorithms for Everyday Use: Weighted Particle Tempering, Practical Reversible Jump, and Extensions. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/71765


Virginia Tech

17. Song, Yuhyun. Linkage Based Dirichlet Processes.

Degree: PhD, Statistics, 2017, Virginia Tech

 We live in the era of textit{Big Data} with significantly richer computational resources than the last two decades. The concurrence of computation resources and a… (more)

Subjects/Keywords: concentration parameter; Dirichlet processes; nested Dirichlet processes

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APA (6th Edition):

Song, Y. (2017). Linkage Based Dirichlet Processes. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/74970

Chicago Manual of Style (16th Edition):

Song, Yuhyun. “Linkage Based Dirichlet Processes.” 2017. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/74970.

MLA Handbook (7th Edition):

Song, Yuhyun. “Linkage Based Dirichlet Processes.” 2017. Web. 07 Apr 2020.

Vancouver:

Song Y. Linkage Based Dirichlet Processes. [Internet] [Doctoral dissertation]. Virginia Tech; 2017. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/74970.

Council of Science Editors:

Song Y. Linkage Based Dirichlet Processes. [Doctoral Dissertation]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/74970


Virginia Tech

18. Seiss, Mark Thomas. Improving Survey Methodology Through Matrix Sampling Design, Integrating Statistical Review Into Data Collection, and Synthetic Estimation Evaluation.

Degree: PhD, Statistics, 2014, Virginia Tech

 The research presented in this dissertation touches on all aspects of survey methodology, from questionnaire design to final estimation. We first approach the questionnaire development… (more)

Subjects/Keywords: Census Coverage Measurement (CCM); Computer Assisted Personal Interviewing (CAPI); Data Editing; Impact Evaluation; Matrix Sampling; Multiple Imputation; On-the-Ground Statistician; Split Questionnaire Design; Synthetic Estimation Error

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APA (6th Edition):

Seiss, M. T. (2014). Improving Survey Methodology Through Matrix Sampling Design, Integrating Statistical Review Into Data Collection, and Synthetic Estimation Evaluation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/47968

Chicago Manual of Style (16th Edition):

Seiss, Mark Thomas. “Improving Survey Methodology Through Matrix Sampling Design, Integrating Statistical Review Into Data Collection, and Synthetic Estimation Evaluation.” 2014. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/47968.

MLA Handbook (7th Edition):

Seiss, Mark Thomas. “Improving Survey Methodology Through Matrix Sampling Design, Integrating Statistical Review Into Data Collection, and Synthetic Estimation Evaluation.” 2014. Web. 07 Apr 2020.

Vancouver:

Seiss MT. Improving Survey Methodology Through Matrix Sampling Design, Integrating Statistical Review Into Data Collection, and Synthetic Estimation Evaluation. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/47968.

Council of Science Editors:

Seiss MT. Improving Survey Methodology Through Matrix Sampling Design, Integrating Statistical Review Into Data Collection, and Synthetic Estimation Evaluation. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/47968


Virginia Tech

19. 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 April 07, 2020. http://hdl.handle.net/10919/52039.

MLA Handbook (7th Edition):

Cheng, Lulu. “Statistical Methods for Genetic Pathway-Based Data Analysis.” 2013. Web. 07 Apr 2020.

Vancouver:

Cheng L. Statistical Methods for Genetic Pathway-Based Data Analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2020 Apr 07]. 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

20. Zielinski, Jacob Jonathan. Adapting Response Surface Methods for the Optimization of Black-Box Systems.

Degree: PhD, Statistics, 2010, Virginia Tech

 Complex mathematical models are often built to describe a physical process that would otherwise be extremely difficult, too costly or sometimes impossible to analyze. Generally,… (more)

Subjects/Keywords: Optimization; Gaussian Stochastic Process; Computer Experiments; Bayesian; Response Surface; DACE; Kriging

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APA (6th Edition):

Zielinski, J. J. (2010). Adapting Response Surface Methods for the Optimization of Black-Box Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/39295

Chicago Manual of Style (16th Edition):

Zielinski, Jacob Jonathan. “Adapting Response Surface Methods for the Optimization of Black-Box Systems.” 2010. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/39295.

MLA Handbook (7th Edition):

Zielinski, Jacob Jonathan. “Adapting Response Surface Methods for the Optimization of Black-Box Systems.” 2010. Web. 07 Apr 2020.

Vancouver:

Zielinski JJ. Adapting Response Surface Methods for the Optimization of Black-Box Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/39295.

Council of Science Editors:

Zielinski JJ. Adapting Response Surface Methods for the Optimization of Black-Box Systems. [Doctoral Dissertation]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/39295


Virginia Tech

21. 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 April 07, 2020. 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. 07 Apr 2020.

Vancouver:

Roberts LR. Variable Selection and Decision Trees: The DiVaS and ALoVaS Methods. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2020 Apr 07]. 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

22. Sabin, Robert Paul Travers. Multiscale and Dirichlet Methods for Supply Chain Order Simulation.

Degree: PhD, Statistics, 2019, Virginia Tech

 Supply chains are complex systems. Researchers in the Social and Decision Analytics Laboratory (SDAL) at Virginia Tech worked with a major global supply chain company… (more)

Subjects/Keywords: Multiscale; Dirichlet; Bayesian; Supply Chain

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APA (6th Edition):

Sabin, R. P. T. (2019). Multiscale and Dirichlet Methods for Supply Chain Order Simulation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/89099

Chicago Manual of Style (16th Edition):

Sabin, Robert Paul Travers. “Multiscale and Dirichlet Methods for Supply Chain Order Simulation.” 2019. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/89099.

MLA Handbook (7th Edition):

Sabin, Robert Paul Travers. “Multiscale and Dirichlet Methods for Supply Chain Order Simulation.” 2019. Web. 07 Apr 2020.

Vancouver:

Sabin RPT. Multiscale and Dirichlet Methods for Supply Chain Order Simulation. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/89099.

Council of Science Editors:

Sabin RPT. Multiscale and Dirichlet Methods for Supply Chain Order Simulation. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/89099


Virginia Tech

23. Metzger, Thomas Anthony. Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection.

Degree: PhD, Statistics, 2019, Virginia Tech

 Statistical models are a powerful tool for describing a broad range of phenomena in our world. However, many common statistical models may make assumptions that… (more)

Subjects/Keywords: model selection; heteroscedasticity; linear models; Bayesian

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APA (6th Edition):

Metzger, T. A. (2019). Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/93226

Chicago Manual of Style (16th Edition):

Metzger, Thomas Anthony. “Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection.” 2019. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/93226.

MLA Handbook (7th Edition):

Metzger, Thomas Anthony. “Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection.” 2019. Web. 07 Apr 2020.

Vancouver:

Metzger TA. Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/93226.

Council of Science Editors:

Metzger TA. Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/93226

24. Self, Jessica Zeitz. Designing and Evaluating Object-Level Interaction to Support Human-Model Communication in Data Analysis.

Degree: PhD, Computer Science, 2016, Virginia Tech

 High-dimensional data appear in all domains and it is challenging to explore. As the number of dimensions in datasets increases, the harder it becomes to… (more)

Subjects/Keywords: visual analytics; human-computer interaction; interface design; dimension reduction

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APA (6th Edition):

Self, J. Z. (2016). Designing and Evaluating Object-Level Interaction to Support Human-Model Communication in Data Analysis. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/70950

Chicago Manual of Style (16th Edition):

Self, Jessica Zeitz. “Designing and Evaluating Object-Level Interaction to Support Human-Model Communication in Data Analysis.” 2016. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/70950.

MLA Handbook (7th Edition):

Self, Jessica Zeitz. “Designing and Evaluating Object-Level Interaction to Support Human-Model Communication in Data Analysis.” 2016. Web. 07 Apr 2020.

Vancouver:

Self JZ. Designing and Evaluating Object-Level Interaction to Support Human-Model Communication in Data Analysis. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/70950.

Council of Science Editors:

Self JZ. Designing and Evaluating Object-Level Interaction to Support Human-Model Communication in Data Analysis. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/70950

25. Bradel, Lauren C. Multi-Model Semantic Interaction for Scalable Text Analytics.

Degree: PhD, Computer Science, 2015, Virginia Tech

 Learning from text data often involves a loop of tasks that iterate between foraging for information and synthesizing it in incremental hypotheses. Past research has… (more)

Subjects/Keywords: sensemaking; visual analytics; user interaction; visualization

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APA (6th Edition):

Bradel, L. C. (2015). Multi-Model Semantic Interaction for Scalable Text Analytics. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/52785

Chicago Manual of Style (16th Edition):

Bradel, Lauren C. “Multi-Model Semantic Interaction for Scalable Text Analytics.” 2015. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/52785.

MLA Handbook (7th Edition):

Bradel, Lauren C. “Multi-Model Semantic Interaction for Scalable Text Analytics.” 2015. Web. 07 Apr 2020.

Vancouver:

Bradel LC. Multi-Model Semantic Interaction for Scalable Text Analytics. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/52785.

Council of Science Editors:

Bradel LC. Multi-Model Semantic Interaction for Scalable Text Analytics. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/52785


Virginia Tech

26. 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 April 07, 2020. http://hdl.handle.net/10919/28563.

MLA Handbook (7th Edition):

Maiti, Dipayan. “Multiset Model Selection and Averaging, and Interactive Storytelling.” 2012. Web. 07 Apr 2020.

Vancouver:

Maiti D. Multiset Model Selection and Averaging, and Interactive Storytelling. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2020 Apr 07]. 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

27. Liao, Hehuan. Improving microbial fate and transport modeling to support TMDL development in an urban watershed.

Degree: PhD, Biological Systems Engineering, 2015, Virginia Tech

 Pathogen contamination, typically quantified by elevated levels of fecal indicator bacteria (FIB), remains the leading cause of surface water-quality impairments in the United States. Continuous… (more)

Subjects/Keywords: Fecal indicator bacteria; fate and transport; quantitative microbial risk analysis; source tracking; urban watershed; waterborne disease

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APA (6th Edition):

Liao, H. (2015). Improving microbial fate and transport modeling to support TMDL development in an urban watershed. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73315

Chicago Manual of Style (16th Edition):

Liao, Hehuan. “Improving microbial fate and transport modeling to support TMDL development in an urban watershed.” 2015. Doctoral Dissertation, Virginia Tech. Accessed April 07, 2020. http://hdl.handle.net/10919/73315.

MLA Handbook (7th Edition):

Liao, Hehuan. “Improving microbial fate and transport modeling to support TMDL development in an urban watershed.” 2015. Web. 07 Apr 2020.

Vancouver:

Liao H. Improving microbial fate and transport modeling to support TMDL development in an urban watershed. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2020 Apr 07]. Available from: http://hdl.handle.net/10919/73315.

Council of Science Editors:

Liao H. Improving microbial fate and transport modeling to support TMDL development in an urban watershed. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/73315


Virginia Tech

28. 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 April 07, 2020. http://hdl.handle.net/10919/28012.

MLA Handbook (7th Edition):

Chen, Jinsong. “Semiparametric Methods for the Generalized Linear Model.” 2010. Web. 07 Apr 2020.

Vancouver:

Chen J. Semiparametric Methods for the Generalized Linear Model. [Internet] [Doctoral dissertation]. Virginia Tech; 2010. [cited 2020 Apr 07]. 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

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