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Texas A&M University

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

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267

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

APA (6^{th} 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 (16^{th} Edition):

Konomi, Bledar. “Bayesian Spatial Modeling of Complex and High Dimensional Data.” 2012. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267.

MLA Handbook (7^{th} Edition):

Konomi, Bledar. “Bayesian Spatial Modeling of Complex and High Dimensional Data.” 2012. Web. 09 May 2021.

Vancouver:

Konomi B. Bayesian Spatial Modeling of Complex and High Dimensional Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 May 09]. 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

2. 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

URL: http://hdl.handle.net/1969.1/173405

► 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 (6^{th} 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 (16^{th} 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 May 09, 2021. http://hdl.handle.net/1969.1/173405.

MLA Handbook (7^{th} Edition):

Payne, Richard Daniel. “Two-Stage Metropolis Hastings; Bayesian Conditional Density Estimation & Survival Analysis via Partition Modeling, Laplace Approximations, and Efficient Computation.” 2018. Web. 09 May 2021.

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 2021 May 09]. 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

3. De, Debkumar. Essays on Bayesian Time Series and Variable Selection.

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

URL: http://hdl.handle.net/1969.1/152793

► Estimating model parameters in dynamic model continues to be challenge. In my dissertation, we have introduced a Stochastic Approximation based parameter estimation approach under Ensemble…
(more)

Subjects/Keywords: Ensemble Kalman Filter; Stochastic Approximation; Non-parametric Regression; Matrix variate regression; Variable selection

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APA (6^{th} Edition):

De, D. (2014). Essays on Bayesian Time Series and Variable Selection. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/152793

Chicago Manual of Style (16^{th} Edition):

De, Debkumar. “Essays on Bayesian Time Series and Variable Selection.” 2014. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/152793.

MLA Handbook (7^{th} Edition):

De, Debkumar. “Essays on Bayesian Time Series and Variable Selection.” 2014. Web. 09 May 2021.

Vancouver:

De D. Essays on Bayesian Time Series and Variable Selection. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/152793.

Council of Science Editors:

De D. Essays on Bayesian Time Series and Variable Selection. [Doctoral Dissertation]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/152793

Texas A&M University

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

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

URL: http://hdl.handle.net/1969.1/148056

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

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

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APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Zhang, Lin. “Application of Bayesian Hierarchical Models in Genetic Data Analysis.” 2012. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/148056.

MLA Handbook (7^{th} Edition):

Zhang, Lin. “Application of Bayesian Hierarchical Models in Genetic Data Analysis.” 2012. Web. 09 May 2021.

Vancouver:

Zhang L. Application of Bayesian Hierarchical Models in Genetic Data Analysis. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/148056.

Council of Science Editors:

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

Texas A&M University

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

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874

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

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

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APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Xun, Xiaolei. “Statistical Inference in Inverse Problems.” 2012. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874.

MLA Handbook (7^{th} Edition):

Xun, Xiaolei. “Statistical Inference in Inverse Problems.” 2012. Web. 09 May 2021.

Vancouver:

Xun X. Statistical Inference in Inverse Problems. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874.

Council of Science Editors:

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

Texas A&M University

6. Stripling, Hayes Franklin. Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations.

Degree: PhD, Nuclear Engineering, 2013, Texas A&M University

URL: http://hdl.handle.net/1969.1/151312

► Depletion calculations for nuclear reactors model the dynamic coupling between the material composition and neutron flux and help predict reactor performance and safety characteristics. In…
(more)

Subjects/Keywords: Adjoint; Sensitivity Analysis; Uncertainty Quantification; Depletion Calculations

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APA (6^{th} Edition):

Stripling, H. F. (2013). Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/151312

Chicago Manual of Style (16^{th} Edition):

Stripling, Hayes Franklin. “Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations.” 2013. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/151312.

MLA Handbook (7^{th} Edition):

Stripling, Hayes Franklin. “Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations.” 2013. Web. 09 May 2021.

Vancouver:

Stripling HF. Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/151312.

Council of Science Editors:

Stripling HF. Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/151312

Texas A&M University

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

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

URL: http://hdl.handle.net/1969.1/161236

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

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

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

APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Wei, Rubin. “Highly Nonlinear Measurement Error Models in Nutritional Epidemiology.” 2014. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/161236.

MLA Handbook (7^{th} Edition):

Wei, Rubin. “Highly Nonlinear Measurement Error Models in Nutritional Epidemiology.” 2014. Web. 09 May 2021.

Vancouver:

Wei R. Highly Nonlinear Measurement Error Models in Nutritional Epidemiology. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/161236.

Council of Science Editors:

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

Texas A&M University

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

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

URL: http://hdl.handle.net/1969.1/153327

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

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

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

APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Sarkar, Abhra. “Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors.” 2014. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/153327.

MLA Handbook (7^{th} Edition):

Sarkar, Abhra. “Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors.” 2014. Web. 09 May 2021.

Vancouver:

Sarkar A. Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors. [Internet] [Doctoral dissertation]. Texas A&M University; 2014. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/153327.

Council of Science Editors:

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

Texas A&M University

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

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

URL: http://hdl.handle.net/1969.1/155108

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

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

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APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Goddard, Scott D. “Restricted Most Powerful Bayesian Tests.” 2015. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/155108.

MLA Handbook (7^{th} Edition):

Goddard, Scott D. “Restricted Most Powerful Bayesian Tests.” 2015. Web. 09 May 2021.

Vancouver:

Goddard SD. Restricted Most Powerful Bayesian Tests. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/155108.

Council of Science Editors:

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

Texas A&M University

10. Hetzler, Adam C. Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem.

Degree: PhD, Nuclear Engineering, 2013, Texas A&M University

URL: http://hdl.handle.net/1969.1/149343

► This research presents new physics-based methods to estimate predictive uncertainty stemming from uncertainty in the material opacities in radiative transfer computations of key quantities of…
(more)

Subjects/Keywords: Uncertainty Quantification; Sensitivity Analysis

Record Details Similar Records

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APA (6^{th} Edition):

Hetzler, A. C. (2013). Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/149343

Chicago Manual of Style (16^{th} Edition):

Hetzler, Adam C. “Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem.” 2013. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/149343.

MLA Handbook (7^{th} Edition):

Hetzler, Adam C. “Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem.” 2013. Web. 09 May 2021.

Vancouver:

Hetzler AC. Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem. [Internet] [Doctoral dissertation]. Texas A&M University; 2013. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/149343.

Council of Science Editors:

Hetzler AC. Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem. [Doctoral Dissertation]. Texas A&M University; 2013. Available from: http://hdl.handle.net/1969.1/149343

Texas A&M University

11. Alahmadi, Hasan Ali H. A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia.

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

URL: http://hdl.handle.net/1969.1/157993

► An energy producer must determine optimal energy investment strategies in order to maximize the value of its energy portfolio. Determining optimal investment strategies is challenging.…
(more)

Subjects/Keywords: Energy Optimization; Uncertainty Quantification; Probabilistic Energy Modeling; Energy Economics

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APA (6^{th} Edition):

Alahmadi, H. A. H. (2016). A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157993

Chicago Manual of Style (16^{th} Edition):

Alahmadi, Hasan Ali H. “A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia.” 2016. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/157993.

MLA Handbook (7^{th} Edition):

Alahmadi, Hasan Ali H. “A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia.” 2016. Web. 09 May 2021.

Vancouver:

Alahmadi HAH. A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/157993.

Council of Science Editors:

Alahmadi HAH. A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157993

Texas A&M University

12. Talluri, Rajesh. Bayesian Gaussian Graphical models using sparse selection priors and their mixtures.

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828

► We propose Bayesian methods for estimating the precision matrix in Gaussian graphical models. The methods lead to sparse and adaptively shrunk estimators of the precision…
(more)

Subjects/Keywords: Bayesian; Gaussian Graphical Models; Covariance Selection; Mixture Models

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APA (6^{th} Edition):

Talluri, R. (2012). Bayesian Gaussian Graphical models using sparse selection priors and their mixtures. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828

Chicago Manual of Style (16^{th} Edition):

Talluri, Rajesh. “Bayesian Gaussian Graphical models using sparse selection priors and their mixtures.” 2012. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828.

MLA Handbook (7^{th} Edition):

Talluri, Rajesh. “Bayesian Gaussian Graphical models using sparse selection priors and their mixtures.” 2012. Web. 09 May 2021.

Vancouver:

Talluri R. Bayesian Gaussian Graphical models using sparse selection priors and their mixtures. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828.

Council of Science Editors:

Talluri R. Bayesian Gaussian Graphical models using sparse selection priors and their mixtures. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828

Texas A&M University

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

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

URL: http://hdl.handle.net/1969.1/155719

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

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

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APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Rahman, Shahina. “Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies.” 2015. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/155719.

MLA Handbook (7^{th} Edition):

Rahman, Shahina. “Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies.” 2015. Web. 09 May 2021.

Vancouver:

Rahman S. Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies. [Internet] [Doctoral dissertation]. Texas A&M University; 2015. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/155719.

Council of Science Editors:

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

Texas A&M University

14. Vyas, Aditya. Application of Machine Learning in Well Performance Prediction, Design Optimization and History Matching.

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

URL: http://hdl.handle.net/1969.1/187248

► Finite difference based reservoir simulation is commonly used to predict well rates in these reservoirs. Such detailed simulation requires an accurate knowledge of reservoir geology.…
(more)

Subjects/Keywords: Unconventional Reservoirs; Machine Learning; Data Analytics; Decline Curves; Hydraulic Fracture Optimization; History Matching

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APA (6^{th} Edition):

Vyas, A. (2017). Application of Machine Learning in Well Performance Prediction, Design Optimization and History Matching. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/187248

Chicago Manual of Style (16^{th} Edition):

Vyas, Aditya. “Application of Machine Learning in Well Performance Prediction, Design Optimization and History Matching.” 2017. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/187248.

MLA Handbook (7^{th} Edition):

Vyas, Aditya. “Application of Machine Learning in Well Performance Prediction, Design Optimization and History Matching.” 2017. Web. 09 May 2021.

Vancouver:

Vyas A. Application of Machine Learning in Well Performance Prediction, Design Optimization and History Matching. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/187248.

Council of Science Editors:

Vyas A. Application of Machine Learning in Well Performance Prediction, Design Optimization and History Matching. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/187248

15. Stripling, Hayes Franklin. The Method of Manufactured Universes for Testing Uncertainty Quantification Methods.

Degree: MS, Nuclear Engineering, 2011, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8986

► The Method of Manufactured Universes is presented as a validation framework for uncertainty quantification (UQ) methodologies and as a tool for exploring the effects of…
(more)

Subjects/Keywords: Uncertainty Quantification; Validation; Bayesian Inversion; Calibration

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

APA (6^{th} Edition):

Stripling, H. F. (2011). The Method of Manufactured Universes for Testing Uncertainty Quantification Methods. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8986

Chicago Manual of Style (16^{th} Edition):

Stripling, Hayes Franklin. “The Method of Manufactured Universes for Testing Uncertainty Quantification Methods.” 2011. Masters Thesis, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8986.

MLA Handbook (7^{th} Edition):

Stripling, Hayes Franklin. “The Method of Manufactured Universes for Testing Uncertainty Quantification Methods.” 2011. Web. 09 May 2021.

Vancouver:

Stripling HF. The Method of Manufactured Universes for Testing Uncertainty Quantification Methods. [Internet] [Masters thesis]. Texas A&M University; 2011. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8986.

Council of Science Editors:

Stripling HF. The Method of Manufactured Universes for Testing Uncertainty Quantification Methods. [Masters Thesis]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8986

16. Humbird, Kelli Denise. Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion.

Degree: MS, Nuclear Engineering, 2016, Texas A&M University

URL: http://hdl.handle.net/1969.1/157147

► Uncertainty quantiﬁcation and sensitivity analysis (UQSA) is becoming an essential component for engineering and physics modeling. The growth of UQSA can be attributed to improved…
(more)

Subjects/Keywords: Adjoint; Sensitivity; Flux Limited Diffusion

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APA (6^{th} Edition):

Humbird, K. D. (2016). Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/157147

Chicago Manual of Style (16^{th} Edition):

Humbird, Kelli Denise. “Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion.” 2016. Masters Thesis, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/157147.

MLA Handbook (7^{th} Edition):

Humbird, Kelli Denise. “Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion.” 2016. Web. 09 May 2021.

Vancouver:

Humbird KD. Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion. [Internet] [Masters thesis]. Texas A&M University; 2016. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/157147.

Council of Science Editors:

Humbird KD. Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion. [Masters Thesis]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/157147

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

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

URL: http://hdl.handle.net/1969.1/2398

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

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

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

APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Ryu, Duchwan. “Regression analysis with longitudinal measurements.” 2005. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/2398.

MLA Handbook (7^{th} Edition):

Ryu, Duchwan. “Regression analysis with longitudinal measurements.” 2005. Web. 09 May 2021.

Vancouver:

Ryu D. Regression analysis with longitudinal measurements. [Internet] [Doctoral dissertation]. Texas A&M University; 2005. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/2398.

Council of Science Editors:

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

18. Chowdhury, Nilanjan Dutta. Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines.

Degree: MS, Industrial Engineering, 2006, Texas A&M University

URL: http://hdl.handle.net/1969.1/3302

► Dual head placement machines are commonly used in industry for placing components on circuit cards with great speed and accuracy. This thesis evaluates a novel…
(more)

Subjects/Keywords: Dual Head Placement Machines; Circuit Card; Process Planning; Column Generation

Record Details Similar Records

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

APA (6^{th} Edition):

Chowdhury, N. D. (2006). Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/3302

Chicago Manual of Style (16^{th} Edition):

Chowdhury, Nilanjan Dutta. “Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines.” 2006. Masters Thesis, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/3302.

MLA Handbook (7^{th} Edition):

Chowdhury, Nilanjan Dutta. “Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines.” 2006. Web. 09 May 2021.

Vancouver:

Chowdhury ND. Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines. [Internet] [Masters thesis]. Texas A&M University; 2006. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/3302.

Council of Science Editors:

Chowdhury ND. Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines. [Masters Thesis]. Texas A&M University; 2006. Available from: http://hdl.handle.net/1969.1/3302

19. Wang, Xiaohui. Bayesian classification and survival analysis with curve predictors.

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-1205

► We propose classification models for binary and multicategory data where the predictor is a random function. The functional predictor could be irregularly and sparsely sampled…
(more)

Subjects/Keywords: smoothing spline; wavelets; hierarchical modeling; generalized linear model; proportional hazards model

Record Details Similar Records

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

APA (6^{th} Edition):

Wang, X. (2009). Bayesian classification and survival analysis with curve predictors. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-1205

Chicago Manual of Style (16^{th} Edition):

Wang, Xiaohui. “Bayesian classification and survival analysis with curve predictors.” 2009. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-1205.

MLA Handbook (7^{th} Edition):

Wang, Xiaohui. “Bayesian classification and survival analysis with curve predictors.” 2009. Web. 09 May 2021.

Vancouver:

Wang X. Bayesian classification and survival analysis with curve predictors. [Internet] [Doctoral dissertation]. Texas A&M University; 2009. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1205.

Council of Science Editors:

Wang X. Bayesian classification and survival analysis with curve predictors. [Doctoral Dissertation]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1205

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

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659

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

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

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

APA (6^{th} Edition):

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

Chicago Manual of Style (16^{th} Edition):

Dhavala, Soma Sekhar. “Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression.” 2012. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659.

MLA Handbook (7^{th} Edition):

Dhavala, Soma Sekhar. “Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression.” 2012. Web. 09 May 2021.

Vancouver:

Dhavala SS. Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659.

Council of Science Editors:

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

21. Lee, Kyeong Eun. Bayesian models for DNA microarray data analysis.

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

URL: http://hdl.handle.net/1969.1/2465

► Selection of signi?cant genes via expression patterns is important in a microarray problem. Owing to small sample size and large number of variables (genes), the…
(more)

Subjects/Keywords: DNA microarray; Bayesian Variable Selection; Probit Regression Model; Weibull Regression Model; Cox's Proportional Hazard Model; Survival Analysis; Curve Clustering; Mixture of Dirichlet Processes; Wavelet

Record Details Similar Records

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

APA (6^{th} Edition):

Lee, K. E. (2005). Bayesian models for DNA microarray data analysis. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/2465

Chicago Manual of Style (16^{th} Edition):

Lee, Kyeong Eun. “Bayesian models for DNA microarray data analysis.” 2005. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/2465.

MLA Handbook (7^{th} Edition):

Lee, Kyeong Eun. “Bayesian models for DNA microarray data analysis.” 2005. Web. 09 May 2021.

Vancouver:

Lee KE. Bayesian models for DNA microarray data analysis. [Internet] [Doctoral dissertation]. Texas A&M University; 2005. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/2465.

Council of Science Editors:

Lee KE. Bayesian models for DNA microarray data analysis. [Doctoral Dissertation]. Texas A&M University; 2005. Available from: http://hdl.handle.net/1969.1/2465

22. Mondal, Anirban. Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems.

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905

► We considered a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a high dimension spatial field. The Bayesian approach contains a…
(more)

Subjects/Keywords: Bayesian Hierarchical Model; Karhunen Loeve Expansion; Two Stage Reversible Jump Markov Chain Monte Carlo; Discrete Cosine Transform; Emulator; Bayesian Multivariate Adaptive Regression Splines

Record Details Similar Records

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

APA (6^{th} Edition):

Mondal, A. (2012). Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905

Chicago Manual of Style (16^{th} Edition):

Mondal, Anirban. “Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems.” 2012. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905.

MLA Handbook (7^{th} Edition):

Mondal, Anirban. “Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems.” 2012. Web. 09 May 2021.

Vancouver:

Mondal A. Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905.

Council of Science Editors:

Mondal A. Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905

23. Hartman, Brian Matthew. Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion.

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8294

► Global marketing managers are keenly interested in being able to predict the sales of their new products. Understanding how a product is adopted over time…
(more)

Subjects/Keywords: Bayesian Methods; Nonparametrics; International New Product Diffusion; Bayesian Adaptive Regression Splines; Hierarchical Models

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

APA (6^{th} Edition):

Hartman, B. M. (2011). Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8294

Chicago Manual of Style (16^{th} Edition):

Hartman, Brian Matthew. “Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion.” 2011. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8294.

MLA Handbook (7^{th} Edition):

Hartman, Brian Matthew. “Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion.” 2011. Web. 09 May 2021.

Vancouver:

Hartman BM. Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8294.

Council of Science Editors:

Hartman BM. Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8294

24. Humbird, Kelli Denise. Machine Learning Guided Discovery and Design for Inertial Confinement Fusion.

Degree: PhD, Nuclear Engineering, 2019, Texas A&M University

URL: http://hdl.handle.net/1969.1/184398

► Inertial conﬁnement fusion (ICF) experiments at the National Ignition Facility (NIF) and their corresponding computer simulations produce an immense amount of rich data. However, quantitatively…
(more)

Subjects/Keywords: inertial confinement fusion; machine learning; deep learning; neural networks; model calibration; predictive modeling

Record Details Similar Records

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

APA (6^{th} Edition):

Humbird, K. D. (2019). Machine Learning Guided Discovery and Design for Inertial Confinement Fusion. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/184398

Chicago Manual of Style (16^{th} Edition):

Humbird, Kelli Denise. “Machine Learning Guided Discovery and Design for Inertial Confinement Fusion.” 2019. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/184398.

MLA Handbook (7^{th} Edition):

Humbird, Kelli Denise. “Machine Learning Guided Discovery and Design for Inertial Confinement Fusion.” 2019. Web. 09 May 2021.

Vancouver:

Humbird KD. Machine Learning Guided Discovery and Design for Inertial Confinement Fusion. [Internet] [Doctoral dissertation]. Texas A&M University; 2019. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/184398.

Council of Science Editors:

Humbird KD. Machine Learning Guided Discovery and Design for Inertial Confinement Fusion. [Doctoral Dissertation]. Texas A&M University; 2019. Available from: http://hdl.handle.net/1969.1/184398

25. Shrivastava, Abhishek Kumar. Listing Unique Fractional Factorial Designs.

Degree: PhD, Industrial Engineering, 2011, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7345

► Fractional factorial designs are a popular choice in designing experiments for studying the effects of multiple factors simultaneously. The first step in planning an experiment…
(more)

Subjects/Keywords: regular fractional factorial designs; graph isomorphism; split-plot designs; design automorphism; design isomorphism; graphs; large run-size design catalogs

Record Details Similar Records

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

APA (6^{th} Edition):

Shrivastava, A. K. (2011). Listing Unique Fractional Factorial Designs. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7345

Chicago Manual of Style (16^{th} Edition):

Shrivastava, Abhishek Kumar. “Listing Unique Fractional Factorial Designs.” 2011. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7345.

MLA Handbook (7^{th} Edition):

Shrivastava, Abhishek Kumar. “Listing Unique Fractional Factorial Designs.” 2011. Web. 09 May 2021.

Vancouver:

Shrivastava AK. Listing Unique Fractional Factorial Designs. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7345.

Council of Science Editors:

Shrivastava AK. Listing Unique Fractional Factorial Designs. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7345

Texas A&M University

26. Parikh, Harshal. Reservoir characterization using experimental design and response surface methodology.

Degree: MS, Petroleum Engineering, 2004, Texas A&M University

URL: http://hdl.handle.net/1969.1/480

► This research combines a statistical tool called experimental design/response surface methodology with reservoir modeling and flow simulation for the purpose of reservoir characterization. Very often,…
(more)

Subjects/Keywords: Experimental Design; Reservoir Characterization

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

APA (6^{th} Edition):

Parikh, H. (2004). Reservoir characterization using experimental design and response surface methodology. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/480

Chicago Manual of Style (16^{th} Edition):

Parikh, Harshal. “Reservoir characterization using experimental design and response surface methodology.” 2004. Masters Thesis, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/480.

MLA Handbook (7^{th} Edition):

Parikh, Harshal. “Reservoir characterization using experimental design and response surface methodology.” 2004. Web. 09 May 2021.

Vancouver:

Parikh H. Reservoir characterization using experimental design and response surface methodology. [Internet] [Masters thesis]. Texas A&M University; 2004. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/480.

Council of Science Editors:

Parikh H. Reservoir characterization using experimental design and response surface methodology. [Masters Thesis]. Texas A&M University; 2004. Available from: http://hdl.handle.net/1969.1/480

Texas A&M University

27. Lee, Ho-Jin. Functional data analysis: classification and regression.

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

URL: http://hdl.handle.net/1969.1/2805

► Functional data refer to data which consist of observed functions or curves evaluated at a finite subset of some interval. In this dissertation, we discuss…
(more)

Subjects/Keywords: Functional data; Support Vector Machine; Principal component analysis; Functional regression; Dimension reduction

Record Details Similar Records

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

APA (6^{th} Edition):

Lee, H. (2005). Functional data analysis: classification and regression. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/2805

Chicago Manual of Style (16^{th} Edition):

Lee, Ho-Jin. “Functional data analysis: classification and regression.” 2005. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/2805.

MLA Handbook (7^{th} Edition):

Lee, Ho-Jin. “Functional data analysis: classification and regression.” 2005. Web. 09 May 2021.

Vancouver:

Lee H. Functional data analysis: classification and regression. [Internet] [Doctoral dissertation]. Texas A&M University; 2005. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/2805.

Council of Science Editors:

Lee H. Functional data analysis: classification and regression. [Doctoral Dissertation]. Texas A&M University; 2005. Available from: http://hdl.handle.net/1969.1/2805

Texas A&M University

28.
Luo, Wen.
Reliability characterization and prediction of high *k* dielectric thin film.

Degree: PhD, Industrial Engineering, 2006, Texas A&M University

URL: http://hdl.handle.net/1969.1/3225

► As technologies continue advancing, semiconductor devices with dimensions in nanometers have entered all spheres of human life. This research deals with both the statistical aspect…
(more)

Subjects/Keywords: Reliability; high k dielectric; dielectric thin film; reliability prediction; breakdown

Record Details Similar Records

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

APA (6^{th} Edition):

Luo, W. (2006). Reliability characterization and prediction of high k dielectric thin film. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/3225

Chicago Manual of Style (16^{th} Edition):

Luo, Wen. “Reliability characterization and prediction of high k dielectric thin film.” 2006. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/3225.

MLA Handbook (7^{th} Edition):

Luo, Wen. “Reliability characterization and prediction of high k dielectric thin film.” 2006. Web. 09 May 2021.

Vancouver:

Luo W. Reliability characterization and prediction of high k dielectric thin film. [Internet] [Doctoral dissertation]. Texas A&M University; 2006. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/3225.

Council of Science Editors:

Luo W. Reliability characterization and prediction of high k dielectric thin film. [Doctoral Dissertation]. Texas A&M University; 2006. Available from: http://hdl.handle.net/1969.1/3225

Texas A&M University

29. Chang, Ilsung. Bayesian inference on mixture models and their applications.

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

URL: http://hdl.handle.net/1969.1/3990

► Mixture models are useful in describing a wide variety of random phenomena because of their flexibility in modeling. They have continued to receive increasing attention…
(more)

Subjects/Keywords: Mixture model; Skew-normal distribution

Record Details Similar Records

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

APA (6^{th} Edition):

Chang, I. (2006). Bayesian inference on mixture models and their applications. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/3990

Chicago Manual of Style (16^{th} Edition):

Chang, Ilsung. “Bayesian inference on mixture models and their applications.” 2006. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/3990.

MLA Handbook (7^{th} Edition):

Chang, Ilsung. “Bayesian inference on mixture models and their applications.” 2006. Web. 09 May 2021.

Vancouver:

Chang I. Bayesian inference on mixture models and their applications. [Internet] [Doctoral dissertation]. Texas A&M University; 2006. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/3990.

Council of Science Editors:

Chang I. Bayesian inference on mixture models and their applications. [Doctoral Dissertation]. Texas A&M University; 2006. Available from: http://hdl.handle.net/1969.1/3990

Texas A&M University

30. Xia, Haifeng. Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.

Degree: PhD, Industrial Engineering, 2010, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164

► This dissertation presents a Bayesian hierarchical model to combine two-resolution metrology data for inspecting the geometric quality of manufactured parts. The high- resolution data points…
(more)

Subjects/Keywords: Bayesian hierarchical model; Bayesian model averaging; Data combining; Gaussian process; Misalignment; Two-resolution data

Record Details Similar Records

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

APA (6^{th} Edition):

Xia, H. (2010). Bayesian Hierarchical Model for Combining Two-resolution Metrology Data. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164

Chicago Manual of Style (16^{th} Edition):

Xia, Haifeng. “Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.” 2010. Doctoral Dissertation, Texas A&M University. Accessed May 09, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164.

MLA Handbook (7^{th} Edition):

Xia, Haifeng. “Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.” 2010. Web. 09 May 2021.

Vancouver:

Xia H. Bayesian Hierarchical Model for Combining Two-resolution Metrology Data. [Internet] [Doctoral dissertation]. Texas A&M University; 2010. [cited 2021 May 09]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164.

Council of Science Editors:

Xia H. Bayesian Hierarchical Model for Combining Two-resolution Metrology Data. [Doctoral Dissertation]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164