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You searched for +publisher:"Texas A&M University" +contributor:("Huang, Jianhua"). Showing records 1 – 30 of 48 total matches.

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Texas A&M University

1. Zhang, Peizhao. Accurate Human Motion Capture and Modeling using Low-cost Sensors.

Degree: PhD, Computer Science, 2017, Texas A&M University

 Motion capture technologies, especially those combined with multiple kinds of sensory technologies to capture both kinematic and dynamic information, are widely used in a variety… (more)

Subjects/Keywords: motion capture; human body tracking; physics-based modeling; full-body shape modeling; hand shape modeling; parametric hand model; non-rigid regirstration

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APA (6th Edition):

Zhang, P. (2017). Accurate Human Motion Capture and Modeling using Low-cost Sensors. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161285

Chicago Manual of Style (16th Edition):

Zhang, Peizhao. “Accurate Human Motion Capture and Modeling using Low-cost Sensors.” 2017. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/161285.

MLA Handbook (7th Edition):

Zhang, Peizhao. “Accurate Human Motion Capture and Modeling using Low-cost Sensors.” 2017. Web. 27 Sep 2020.

Vancouver:

Zhang P. Accurate Human Motion Capture and Modeling using Low-cost Sensors. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/161285.

Council of Science Editors:

Zhang P. Accurate Human Motion Capture and Modeling using Low-cost Sensors. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161285


Texas A&M University

2. Hu, Jiaxi. Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN.

Degree: PhD, Atmospheric Sciences, 2018, Texas A&M University

 Hypotheses have been proposed for decades about cloud condensation nuclei (CCN) aerosol effect on delaying the warm rain process, invigorating deep convective cloud vertical development,… (more)

Subjects/Keywords: Aerosol-cloud interactions; cloud electrification; weather modification

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APA (6th Edition):

Hu, J. (2018). Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173788

Chicago Manual of Style (16th Edition):

Hu, Jiaxi. “Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN.” 2018. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173788.

MLA Handbook (7th Edition):

Hu, Jiaxi. “Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN.” 2018. Web. 27 Sep 2020.

Vancouver:

Hu J. Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173788.

Council of Science Editors:

Hu J. Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173788


Texas A&M University

3. Shin, Yei Eun. Statistical Research on Covariate Matching, Monotone Functional Data and Binary Spatio-temporal Data Modeling.

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

 This dissertation consists of three studies in different fields. (1) The first study aims to evaluate the effect of wind turbine upgrades by devising a… (more)

Subjects/Keywords: Matching methods; Observational study; Causal inference; Wind power analysis; Monotone curves; Functional data analysis; Principal component analysis; Autologistic regression; Pseudo likelihood; Graph structure; ALS disease analysis

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APA (6th Edition):

Shin, Y. E. (2017). Statistical Research on Covariate Matching, Monotone Functional Data and Binary Spatio-temporal Data Modeling. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/187243

Chicago Manual of Style (16th Edition):

Shin, Yei Eun. “Statistical Research on Covariate Matching, Monotone Functional Data and Binary Spatio-temporal Data Modeling.” 2017. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/187243.

MLA Handbook (7th Edition):

Shin, Yei Eun. “Statistical Research on Covariate Matching, Monotone Functional Data and Binary Spatio-temporal Data Modeling.” 2017. Web. 27 Sep 2020.

Vancouver:

Shin YE. Statistical Research on Covariate Matching, Monotone Functional Data and Binary Spatio-temporal Data Modeling. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/187243.

Council of Science Editors:

Shin YE. Statistical Research on Covariate Matching, Monotone Functional Data and Binary Spatio-temporal Data Modeling. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/187243


Texas A&M University

4. Qian, Yanjun. Data Science Methods for Analyzing Nanomaterial Images and Videos.

Degree: PhD, Industrial Engineering, 2018, Texas A&M University

 A large amount of nanomaterial characterization data has been routinely collected by using electron microscopes and stored in image or video formats. A bottleneck in… (more)

Subjects/Keywords: In situ TEM video; nanoparticle growth process; change point detection; time-varying probability density functions estimation

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APA (6th Edition):

Qian, Y. (2018). Data Science Methods for Analyzing Nanomaterial Images and Videos. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173896

Chicago Manual of Style (16th Edition):

Qian, Yanjun. “Data Science Methods for Analyzing Nanomaterial Images and Videos.” 2018. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173896.

MLA Handbook (7th Edition):

Qian, Yanjun. “Data Science Methods for Analyzing Nanomaterial Images and Videos.” 2018. Web. 27 Sep 2020.

Vancouver:

Qian Y. Data Science Methods for Analyzing Nanomaterial Images and Videos. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173896.

Council of Science Editors:

Qian Y. Data Science Methods for Analyzing Nanomaterial Images and Videos. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173896


Texas A&M University

5. Zhang, Bohai. Statistical Methods for Large Spatial and Spatio-temporal Datasets.

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

 Classical statistical models encounter the computational bottleneck for large spatial/spatio-temporal datasets. This dissertation contains three articles describing computationally efficient approximation methods for applying Gaussian process… (more)

Subjects/Keywords: Spatial statistics; spatio-temporal statistics; Gaussian process; covariance matrix; conditional likelihood; uncertainty quantification

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APA (6th Edition):

Zhang, B. (2015). Statistical Methods for Large Spatial and Spatio-temporal Datasets. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/187445

Chicago Manual of Style (16th Edition):

Zhang, Bohai. “Statistical Methods for Large Spatial and Spatio-temporal Datasets.” 2015. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/187445.

MLA Handbook (7th Edition):

Zhang, Bohai. “Statistical Methods for Large Spatial and Spatio-temporal Datasets.” 2015. Web. 27 Sep 2020.

Vancouver:

Zhang B. Statistical Methods for Large Spatial and Spatio-temporal Datasets. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/187445.

Council of Science Editors:

Zhang B. Statistical Methods for Large Spatial and Spatio-temporal Datasets. [Doctoral Dissertation]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/187445


Texas A&M University

6. He, Shiyuan. Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination.

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

 Both type Ia supernovae and variable stars are important distance indicators in astronomy. The peak luminosity of type Ia supernovae and the period-luminosity relation of… (more)

Subjects/Keywords: functional data; type Ia supernova; Mira variable

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APA (6th Edition):

He, S. (2017). Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161496

Chicago Manual of Style (16th Edition):

He, Shiyuan. “Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination.” 2017. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/161496.

MLA Handbook (7th Edition):

He, Shiyuan. “Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination.” 2017. Web. 27 Sep 2020.

Vancouver:

He S. Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/161496.

Council of Science Editors:

He S. Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161496


Texas A&M University

7. Tran, Hoang Minh. Data Driven Techniques for Modeling Coupled Dynamics in Transient Processes.

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

 We study the problem of modeling coupled dynamics in transient processes that happen in a network. The problem is considered at two levels. At the… (more)

Subjects/Keywords: coupled dynamics; network inference; change detection; direct influence; nonlinear time series

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APA (6th Edition):

Tran, H. M. (2017). Data Driven Techniques for Modeling Coupled Dynamics in Transient Processes. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/165837

Chicago Manual of Style (16th Edition):

Tran, Hoang Minh. “Data Driven Techniques for Modeling Coupled Dynamics in Transient Processes.” 2017. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/165837.

MLA Handbook (7th Edition):

Tran, Hoang Minh. “Data Driven Techniques for Modeling Coupled Dynamics in Transient Processes.” 2017. Web. 27 Sep 2020.

Vancouver:

Tran HM. Data Driven Techniques for Modeling Coupled Dynamics in Transient Processes. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/165837.

Council of Science Editors:

Tran HM. Data Driven Techniques for Modeling Coupled Dynamics in Transient Processes. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/165837


Texas A&M University

8. Konomi, Bledar. Bayesian Spatial Modeling of Complex and High Dimensional Data.

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

 The main objective of this dissertation is to apply Bayesian modeling to different complex and high-dimensional spatial data sets. I develop Bayesian hierarchical spatial models… (more)

Subjects/Keywords: Object classification; Image segmentation; Nanoparticles; Markov-chain Monte-carlo; Bayesian shape analysis; Predictive process; Full-scale approximation; Bayesian treed Gaussian process

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APA (6th Edition):

Konomi, B. (2012). Bayesian Spatial Modeling of Complex and High Dimensional Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267

Chicago Manual of Style (16th Edition):

Konomi, Bledar. “Bayesian Spatial Modeling of Complex and High Dimensional Data.” 2012. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267.

MLA Handbook (7th Edition):

Konomi, Bledar. “Bayesian Spatial Modeling of Complex and High Dimensional Data.” 2012. Web. 27 Sep 2020.

Vancouver:

Konomi B. Bayesian Spatial Modeling of Complex and High Dimensional Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267.

Council of Science Editors:

Konomi B. Bayesian Spatial Modeling of Complex and High Dimensional Data. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267


Texas A&M University

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

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

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

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

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Xu, Ganggang. “Variable Selection and Function Estimation Using Penalized Methods.” 2012. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10451.

MLA Handbook (7th Edition):

Xu, Ganggang. “Variable Selection and Function Estimation Using Penalized Methods.” 2012. Web. 27 Sep 2020.

Vancouver:

Xu G. Variable Selection and Function Estimation Using Penalized Methods. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10451.

Council of Science Editors:

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


Texas A&M University

10. Zhan, Dongling. The k-Sample Problem When k is Large and n Small.

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

 The k-sample problem, i.e., testing whether two or more data sets come from the same population, is a classic one in statistics. Instead of having… (more)

Subjects/Keywords: K-Sample Problem; Kernel Density Estimation; Asymptotic Normal Distribution; Hypothesis Test; Random Effects

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APA (6th Edition):

Zhan, D. (2012). The k-Sample Problem When k is Large and n Small. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10860

Chicago Manual of Style (16th Edition):

Zhan, Dongling. “The k-Sample Problem When k is Large and n Small.” 2012. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10860.

MLA Handbook (7th Edition):

Zhan, Dongling. “The k-Sample Problem When k is Large and n Small.” 2012. Web. 27 Sep 2020.

Vancouver:

Zhan D. The k-Sample Problem When k is Large and n Small. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10860.

Council of Science Editors:

Zhan D. The k-Sample Problem When k is Large and n Small. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10860


Texas A&M University

11. Lu, Meng. Probabilistic Models for Aggregate Analysis of Non-Gaussian Data in Biomedicine.

Degree: PhD, Computer Engineering, 2015, Texas A&M University

 Aggregate association analysis is a popular way in genome-wide association studies (GWAS) that analyzes the association between the trait of interest and regions of functionally… (more)

Subjects/Keywords: Aggregate association analysis; Genome Wide Association Studies; Sparse Exponential Family PCA; Matched PCA

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APA (6th Edition):

Lu, M. (2015). Probabilistic Models for Aggregate Analysis of Non-Gaussian Data in Biomedicine. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/156478

Chicago Manual of Style (16th Edition):

Lu, Meng. “Probabilistic Models for Aggregate Analysis of Non-Gaussian Data in Biomedicine.” 2015. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/156478.

MLA Handbook (7th Edition):

Lu, Meng. “Probabilistic Models for Aggregate Analysis of Non-Gaussian Data in Biomedicine.” 2015. Web. 27 Sep 2020.

Vancouver:

Lu M. Probabilistic Models for Aggregate Analysis of Non-Gaussian Data in Biomedicine. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/156478.

Council of Science Editors:

Lu M. Probabilistic Models for Aggregate Analysis of Non-Gaussian Data in Biomedicine. [Doctoral Dissertation]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/156478


Texas A&M University

12. Hu, Jiaxi. Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN.

Degree: PhD, Atmospheric Sciences, 2018, Texas A&M University

 Hypotheses have been proposed for decades about cloud condensation nuclei (CCN) aerosol effect on delaying the warm rain process, invigorating deep convective cloud vertical development,… (more)

Subjects/Keywords: Aerosol-cloud interactions; cloud electrification; weather modification

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APA (6th Edition):

Hu, J. (2018). Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173882

Chicago Manual of Style (16th Edition):

Hu, Jiaxi. “Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN.” 2018. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173882.

MLA Handbook (7th Edition):

Hu, Jiaxi. “Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN.” 2018. Web. 27 Sep 2020.

Vancouver:

Hu J. Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173882.

Council of Science Editors:

Hu J. Polarimetric Radar Convective Cell Tracking Reveals Large Sensitivity of Cloud Precipitation and Electrification Properties to CCN. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173882


Texas A&M University

13. Tsai, Chung-Chi. Image Co-Saliency Detection: Novel Approaches with Convex Optimization and Deep Neural Networks.

Degree: PhD, Electrical Engineering, 2018, Texas A&M University

 The advance of digital technologies has endowed people with easier access to massive collections of image or video data than ever before. For its capability… (more)

Subjects/Keywords: Co-saliency detection; co-segmentation; saliency detection; image segmentation; stacked autoencoder; reconstruction residual; adaptive fusion; optimization; self-paced learning; CNNs

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APA (6th Edition):

Tsai, C. (2018). Image Co-Saliency Detection: Novel Approaches with Convex Optimization and Deep Neural Networks. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173679

Chicago Manual of Style (16th Edition):

Tsai, Chung-Chi. “Image Co-Saliency Detection: Novel Approaches with Convex Optimization and Deep Neural Networks.” 2018. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173679.

MLA Handbook (7th Edition):

Tsai, Chung-Chi. “Image Co-Saliency Detection: Novel Approaches with Convex Optimization and Deep Neural Networks.” 2018. Web. 27 Sep 2020.

Vancouver:

Tsai C. Image Co-Saliency Detection: Novel Approaches with Convex Optimization and Deep Neural Networks. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173679.

Council of Science Editors:

Tsai C. Image Co-Saliency Detection: Novel Approaches with Convex Optimization and Deep Neural Networks. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173679


Texas A&M University

14. Wu, Meng. Physics-Based and Data-Driven Analytics for Enhanced Planning and Operations in Power Systems with Deep Renewable Penetration.

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

 This dissertation is motivated by the lack of combined physics-based and data-driven framework for solving power system challenges that are introduced by the integration of… (more)

Subjects/Keywords: phasor measurement unit; bad data detection; wind farm; sub-synchronous oscillation; doubly-fed induction generator; model initialization; power plant model validation; model diagnosis; power system voltage stability.

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APA (6th Edition):

Wu, M. (2017). Physics-Based and Data-Driven Analytics for Enhanced Planning and Operations in Power Systems with Deep Renewable Penetration. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173140

Chicago Manual of Style (16th Edition):

Wu, Meng. “Physics-Based and Data-Driven Analytics for Enhanced Planning and Operations in Power Systems with Deep Renewable Penetration.” 2017. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173140.

MLA Handbook (7th Edition):

Wu, Meng. “Physics-Based and Data-Driven Analytics for Enhanced Planning and Operations in Power Systems with Deep Renewable Penetration.” 2017. Web. 27 Sep 2020.

Vancouver:

Wu M. Physics-Based and Data-Driven Analytics for Enhanced Planning and Operations in Power Systems with Deep Renewable Penetration. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173140.

Council of Science Editors:

Wu M. Physics-Based and Data-Driven Analytics for Enhanced Planning and Operations in Power Systems with Deep Renewable Penetration. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/173140


Texas A&M University

15. Zheng, Qingran. Hybrid Verification for Analog and Mixed-signal Circuits.

Degree: MS, Computer Engineering, 2017, Texas A&M University

 With increasing design complexity and reliability requirements, analog and mixedsignal (AMS) verification manifests itself as a key bottleneck. While formal methods and machine learning have… (more)

Subjects/Keywords: AMS Verification; Formal Verification; Machine Learning

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APA (6th Edition):

Zheng, Q. (2017). Hybrid Verification for Analog and Mixed-signal Circuits. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173237

Chicago Manual of Style (16th Edition):

Zheng, Qingran. “Hybrid Verification for Analog and Mixed-signal Circuits.” 2017. Masters Thesis, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173237.

MLA Handbook (7th Edition):

Zheng, Qingran. “Hybrid Verification for Analog and Mixed-signal Circuits.” 2017. Web. 27 Sep 2020.

Vancouver:

Zheng Q. Hybrid Verification for Analog and Mixed-signal Circuits. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173237.

Council of Science Editors:

Zheng Q. Hybrid Verification for Analog and Mixed-signal Circuits. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/173237


Texas A&M University

16. Payne, Richard Daniel. Two-Stage Metropolis Hastings; Bayesian Conditional Density Estimation & Survival Analysis via Partition Modeling, Laplace Approximations, and Efficient Computation.

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

 Bayesian statistical methods are known for their flexibility in modeling. This flexibility is possible because parameters can often be estimated via Markov chain Monte Carlo… (more)

Subjects/Keywords: Bayesian statistics; Laplace approximation; partition model; Gaussian process; Markov chain Monte Carlo; survival analysis

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APA (6th Edition):

Payne, R. D. (2018). Two-Stage Metropolis Hastings; Bayesian Conditional Density Estimation & Survival Analysis via Partition Modeling, Laplace Approximations, and Efficient Computation. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173405

Chicago Manual of Style (16th Edition):

Payne, Richard Daniel. “Two-Stage Metropolis Hastings; Bayesian Conditional Density Estimation & Survival Analysis via Partition Modeling, Laplace Approximations, and Efficient Computation.” 2018. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173405.

MLA Handbook (7th Edition):

Payne, Richard Daniel. “Two-Stage Metropolis Hastings; Bayesian Conditional Density Estimation & Survival Analysis via Partition Modeling, Laplace Approximations, and Efficient Computation.” 2018. Web. 27 Sep 2020.

Vancouver:

Payne RD. Two-Stage Metropolis Hastings; Bayesian Conditional Density Estimation & Survival Analysis via Partition Modeling, Laplace Approximations, and Efficient Computation. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173405.

Council of Science Editors:

Payne RD. Two-Stage Metropolis Hastings; Bayesian Conditional Density Estimation & Survival Analysis via Partition Modeling, Laplace Approximations, and Efficient Computation. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/173405


Texas A&M University

17. Suya, . A General Approach for Asymptotics of Penalized Spline Estimation in Extended Linear Models.

Degree: PhD, Statistics, 2016, Texas A&M University

 The penalized spline estimator has been formally introduced in the context of the nonparametric regression model. Despite the wide range of its application, the theory… (more)

Subjects/Keywords: Penalized Spline; Convergence Rate; Extended Linear Model

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APA (6th Edition):

Suya, .. (2016). A General Approach for Asymptotics of Penalized Spline Estimation in Extended Linear Models. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157726

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Suya, .. “A General Approach for Asymptotics of Penalized Spline Estimation in Extended Linear Models.” 2016. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/157726.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Suya, .. “A General Approach for Asymptotics of Penalized Spline Estimation in Extended Linear Models.” 2016. Web. 27 Sep 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Suya, .. A General Approach for Asymptotics of Penalized Spline Estimation in Extended Linear Models. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/157726.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Suya, .. A General Approach for Asymptotics of Penalized Spline Estimation in Extended Linear Models. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157726

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


Texas A&M University

18. Li, Hongjun. Three Essays on Semiparametric Econometrics: Theory and Application.

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

 This dissertation aims at investigating the theory and application of semiparametric econometrics. I first inspect the selection of optimal bandwidth using the cross-validation method for… (more)

Subjects/Keywords: Semiparametric; Cross-Validation; Bandwidth Selection; Factor Analysis; Number of Factors; Purchasing Power Parity; Varying Coefficient Models

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APA (6th Edition):

Li, H. (2014). Three Essays on Semiparametric Econometrics: Theory and Application. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/152605

Chicago Manual of Style (16th Edition):

Li, Hongjun. “Three Essays on Semiparametric Econometrics: Theory and Application.” 2014. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/152605.

MLA Handbook (7th Edition):

Li, Hongjun. “Three Essays on Semiparametric Econometrics: Theory and Application.” 2014. Web. 27 Sep 2020.

Vancouver:

Li H. Three Essays on Semiparametric Econometrics: Theory and Application. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/152605.

Council of Science Editors:

Li H. Three Essays on Semiparametric Econometrics: Theory and Application. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/152605


Texas A&M University

19. Pourhabib, Arash. Gaussian Process Modeling and Computation in Engineering Applications.

Degree: PhD, Industrial Engineering, 2014, Texas A&M University

 Big Data refers to the complexity, high-dimensionality, and high volume of information which are common features in many contemporary engineering applications. In the context of… (more)

Subjects/Keywords: Gaussian processes; Multi-fidelity analysis; Spatial-temporal modeling

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APA (6th Edition):

Pourhabib, A. (2014). Gaussian Process Modeling and Computation in Engineering Applications. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153314

Chicago Manual of Style (16th Edition):

Pourhabib, Arash. “Gaussian Process Modeling and Computation in Engineering Applications.” 2014. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/153314.

MLA Handbook (7th Edition):

Pourhabib, Arash. “Gaussian Process Modeling and Computation in Engineering Applications.” 2014. Web. 27 Sep 2020.

Vancouver:

Pourhabib A. Gaussian Process Modeling and Computation in Engineering Applications. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/153314.

Council of Science Editors:

Pourhabib A. Gaussian Process Modeling and Computation in Engineering Applications. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153314


Texas A&M University

20. Feng, Shuo. A Likelihood Based Framework for Data Integration with Application to eQTL Mapping.

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

 We develop a new way of thinking about and integrating gene expression data (continuous) and genomic information data (binary) by jointly compressing the two data… (more)

Subjects/Keywords: Data integration; eQTL; GWAS; CCA

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APA (6th Edition):

Feng, S. (2014). A Likelihood Based Framework for Data Integration with Application to eQTL Mapping. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153318

Chicago Manual of Style (16th Edition):

Feng, Shuo. “A Likelihood Based Framework for Data Integration with Application to eQTL Mapping.” 2014. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/153318.

MLA Handbook (7th Edition):

Feng, Shuo. “A Likelihood Based Framework for Data Integration with Application to eQTL Mapping.” 2014. Web. 27 Sep 2020.

Vancouver:

Feng S. A Likelihood Based Framework for Data Integration with Application to eQTL Mapping. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/153318.

Council of Science Editors:

Feng S. A Likelihood Based Framework for Data Integration with Application to eQTL Mapping. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153318


Texas A&M University

21. Sun, Mengmeng. Regional Climate Effect on Population Abundance of Major Duck Species in Interior Plains of Canada.

Degree: MS, Wildlife and Fisheries Sciences, 2013, Texas A&M University

 Population dynamics of ducks is a complex process influenced by both biotic and abiotic factors, and good understanding about the mechanisms behind this process is… (more)

Subjects/Keywords: climate; population dynamics; duck

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APA (6th Edition):

Sun, M. (2013). Regional Climate Effect on Population Abundance of Major Duck Species in Interior Plains of Canada. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/149518

Chicago Manual of Style (16th Edition):

Sun, Mengmeng. “Regional Climate Effect on Population Abundance of Major Duck Species in Interior Plains of Canada.” 2013. Masters Thesis, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/149518.

MLA Handbook (7th Edition):

Sun, Mengmeng. “Regional Climate Effect on Population Abundance of Major Duck Species in Interior Plains of Canada.” 2013. Web. 27 Sep 2020.

Vancouver:

Sun M. Regional Climate Effect on Population Abundance of Major Duck Species in Interior Plains of Canada. [Internet] [Masters thesis]. Texas A&M University; 2013. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/149518.

Council of Science Editors:

Sun M. Regional Climate Effect on Population Abundance of Major Duck Species in Interior Plains of Canada. [Masters Thesis]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/149518


Texas A&M University

22. Pan, Huijun 1987-. Bivariate B-splines and its Applications in Spatial Data Analysis.

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

 In the field of spatial statistics, it is often desirable to generate a smooth surface for a region over which only noisy observations of the… (more)

Subjects/Keywords: spatial data analysis; smoothing; bivariate splines

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APA (6th Edition):

Pan, H. 1. (2011). Bivariate B-splines and its Applications in Spatial Data Analysis. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/150949

Chicago Manual of Style (16th Edition):

Pan, Huijun 1987-. “Bivariate B-splines and its Applications in Spatial Data Analysis.” 2011. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/150949.

MLA Handbook (7th Edition):

Pan, Huijun 1987-. “Bivariate B-splines and its Applications in Spatial Data Analysis.” 2011. Web. 27 Sep 2020.

Vancouver:

Pan H1. Bivariate B-splines and its Applications in Spatial Data Analysis. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/150949.

Council of Science Editors:

Pan H1. Bivariate B-splines and its Applications in Spatial Data Analysis. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/150949


Texas A&M University

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

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

 Smoothing splines provide flexible nonparametric regression estimators. Penalized likelihood method is adopted when responses are from exponential families and multivariate models are constructed with certain… (more)

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

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Zhang, Nan. “Adaptive Basis Sampling for Smoothing Splines.” 2015. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/155626.

MLA Handbook (7th Edition):

Zhang, Nan. “Adaptive Basis Sampling for Smoothing Splines.” 2015. Web. 27 Sep 2020.

Vancouver:

Zhang N. Adaptive Basis Sampling for Smoothing Splines. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/155626.

Council of Science Editors:

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


Texas A&M University

24. Ge, Hancheng. Tensor Learning for Recovering Missing Information: Algorithms and Applications on Social Media.

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

 Real-time social systems like Facebook, Twitter, and Snapchat have been growing rapidly, producing exabytes of data in different views or aspects. Coupled with more and… (more)

Subjects/Keywords: Tensor Learning; Missing Information; Social Media; Scalable Algorithm

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APA (6th Edition):

Ge, H. (2017). Tensor Learning for Recovering Missing Information: Algorithms and Applications on Social Media. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173209

Chicago Manual of Style (16th Edition):

Ge, Hancheng. “Tensor Learning for Recovering Missing Information: Algorithms and Applications on Social Media.” 2017. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173209.

MLA Handbook (7th Edition):

Ge, Hancheng. “Tensor Learning for Recovering Missing Information: Algorithms and Applications on Social Media.” 2017. Web. 27 Sep 2020.

Vancouver:

Ge H. Tensor Learning for Recovering Missing Information: Algorithms and Applications on Social Media. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173209.

Council of Science Editors:

Ge H. Tensor Learning for Recovering Missing Information: Algorithms and Applications on Social Media. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/173209


Texas A&M University

25. Kim, Jinsu. A Bootstrap Metropolis-Hastings algorithm for Bayesian Analysis of Big Data.

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

 Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their compute-intensive nature, which… (more)

Subjects/Keywords: Bayesian analysis; Big data; Markov chain Monte Carlo; Metropolis Hastings algorithm; Parallel computing; Bootstrap; Sub-sampling

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APA (6th Edition):

Kim, J. (2014). A Bootstrap Metropolis-Hastings algorithm for Bayesian Analysis of Big Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174185

Chicago Manual of Style (16th Edition):

Kim, Jinsu. “A Bootstrap Metropolis-Hastings algorithm for Bayesian Analysis of Big Data.” 2014. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/174185.

MLA Handbook (7th Edition):

Kim, Jinsu. “A Bootstrap Metropolis-Hastings algorithm for Bayesian Analysis of Big Data.” 2014. Web. 27 Sep 2020.

Vancouver:

Kim J. A Bootstrap Metropolis-Hastings algorithm for Bayesian Analysis of Big Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/174185.

Council of Science Editors:

Kim J. A Bootstrap Metropolis-Hastings algorithm for Bayesian Analysis of Big Data. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/174185


Texas A&M University

26. Yuan, Wenlong. Period-Luminosity Relations of Cepheid and Mira Variables and Their Application to the Extragalactic Distance Scale.

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

 In this dissertation, I present work towards accurate and precise distance determinations using both Cepheids and Miras. The work includes a Cepheid search in the… (more)

Subjects/Keywords: Period-Luminosity relations; Miras; Cepheids

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APA (6th Edition):

Yuan, W. (2017). Period-Luminosity Relations of Cepheid and Mira Variables and Their Application to the Extragalactic Distance Scale. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/165719

Chicago Manual of Style (16th Edition):

Yuan, Wenlong. “Period-Luminosity Relations of Cepheid and Mira Variables and Their Application to the Extragalactic Distance Scale.” 2017. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/165719.

MLA Handbook (7th Edition):

Yuan, Wenlong. “Period-Luminosity Relations of Cepheid and Mira Variables and Their Application to the Extragalactic Distance Scale.” 2017. Web. 27 Sep 2020.

Vancouver:

Yuan W. Period-Luminosity Relations of Cepheid and Mira Variables and Their Application to the Extragalactic Distance Scale. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/165719.

Council of Science Editors:

Yuan W. Period-Luminosity Relations of Cepheid and Mira Variables and Their Application to the Extragalactic Distance Scale. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/165719


Texas A&M University

27. Yagi, Daisuke. Theory and Application of Local Weighted Shape Constrained Estimators for Analyzing Census of Manufacturing Data.

Degree: PhD, Industrial Engineering, 2018, Texas A&M University

 Efficiency and productivity analysis focuses on firm performance to obtain firm–level and industry–level economic structural insights. This study provides the theoretical and methodological basis for… (more)

Subjects/Keywords: Productivity analysis; Production economics; Kernel estimation; Local polynomials; Multivariate convex regression; Nonparametric regression; Shape constraints; Instrumental variables

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APA (6th Edition):

Yagi, D. (2018). Theory and Application of Local Weighted Shape Constrained Estimators for Analyzing Census of Manufacturing Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174071

Chicago Manual of Style (16th Edition):

Yagi, Daisuke. “Theory and Application of Local Weighted Shape Constrained Estimators for Analyzing Census of Manufacturing Data.” 2018. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/174071.

MLA Handbook (7th Edition):

Yagi, Daisuke. “Theory and Application of Local Weighted Shape Constrained Estimators for Analyzing Census of Manufacturing Data.” 2018. Web. 27 Sep 2020.

Vancouver:

Yagi D. Theory and Application of Local Weighted Shape Constrained Estimators for Analyzing Census of Manufacturing Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2018. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/174071.

Council of Science Editors:

Yagi D. Theory and Application of Local Weighted Shape Constrained Estimators for Analyzing Census of Manufacturing Data. [Doctoral Dissertation]. Texas A&M University; 2018. Available from: http://hdl.handle.net/1969.1/174071


Texas A&M University

28. Ren, Shaogang. SCALABLE ALGORITHMS FOR HIGH DIMENSIONAL STRUCTURED DATA.

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

 Emerging technologies and digital devices provide us with increasingly large volume of data with respect to both the sample size and the number of features.… (more)

Subjects/Keywords: Sparse Learning; LASSO; Structured Sparse; Scalability; Big Data

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APA (6th Edition):

Ren, S. (2017). SCALABLE ALGORITHMS FOR HIGH DIMENSIONAL STRUCTURED DATA. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173033

Chicago Manual of Style (16th Edition):

Ren, Shaogang. “SCALABLE ALGORITHMS FOR HIGH DIMENSIONAL STRUCTURED DATA.” 2017. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/173033.

MLA Handbook (7th Edition):

Ren, Shaogang. “SCALABLE ALGORITHMS FOR HIGH DIMENSIONAL STRUCTURED DATA.” 2017. Web. 27 Sep 2020.

Vancouver:

Ren S. SCALABLE ALGORITHMS FOR HIGH DIMENSIONAL STRUCTURED DATA. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/173033.

Council of Science Editors:

Ren S. SCALABLE ALGORITHMS FOR HIGH DIMENSIONAL STRUCTURED DATA. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/173033


Texas A&M University

29. Liu, Wei. A New Asset Pricing Model based on the Zero-Beta CAPM: Theory and Evidence.

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

 This work utilizes zero-beta CAPM to derive an alternative form dubbed the ZCAPM. The ZCAPM posits that asset prices are a function of market risk… (more)

Subjects/Keywords: Asset Pricing; Zero-Beta CAPM; Factor Model; Random Matrix Theory

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APA (6th Edition):

Liu, W. (2013). A New Asset Pricing Model based on the Zero-Beta CAPM: Theory and Evidence. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/149521

Chicago Manual of Style (16th Edition):

Liu, Wei. “A New Asset Pricing Model based on the Zero-Beta CAPM: Theory and Evidence.” 2013. Doctoral Dissertation, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/149521.

MLA Handbook (7th Edition):

Liu, Wei. “A New Asset Pricing Model based on the Zero-Beta CAPM: Theory and Evidence.” 2013. Web. 27 Sep 2020.

Vancouver:

Liu W. A New Asset Pricing Model based on the Zero-Beta CAPM: Theory and Evidence. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/149521.

Council of Science Editors:

Liu W. A New Asset Pricing Model based on the Zero-Beta CAPM: Theory and Evidence. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/149521


Texas A&M University

30. Huang, Tong. Optimal PMU Placement and Signal Selection for Monitoring Critical Power System Oscillations.

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

 In this thesis, a strategy for phasor measurement unit (PMU) optimal placement and signal selection is proposed for monitoring critical oscillations in electric power systems.… (more)

Subjects/Keywords: Oscillation monitoring; PMU Placement

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APA (6th Edition):

Huang, T. (2017). Optimal PMU Placement and Signal Selection for Monitoring Critical Power System Oscillations. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/174755

Chicago Manual of Style (16th Edition):

Huang, Tong. “Optimal PMU Placement and Signal Selection for Monitoring Critical Power System Oscillations.” 2017. Masters Thesis, Texas A&M University. Accessed September 27, 2020. http://hdl.handle.net/1969.1/174755.

MLA Handbook (7th Edition):

Huang, Tong. “Optimal PMU Placement and Signal Selection for Monitoring Critical Power System Oscillations.” 2017. Web. 27 Sep 2020.

Vancouver:

Huang T. Optimal PMU Placement and Signal Selection for Monitoring Critical Power System Oscillations. [Internet] [Masters thesis]. Texas A&M University; 2017. [cited 2020 Sep 27]. Available from: http://hdl.handle.net/1969.1/174755.

Council of Science Editors:

Huang T. Optimal PMU Placement and Signal Selection for Monitoring Critical Power System Oscillations. [Masters Thesis]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/174755

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