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You searched for +publisher:"Texas A&M University" +contributor:("Mallick, Bani K"). Showing records 1 – 30 of 39 total matches.

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Texas A&M University

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

Degree: 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. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Konomi, Bledar. “Bayesian Spatial Modeling of Complex and High Dimensional Data.” 2012. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Konomi, Bledar. “Bayesian Spatial Modeling of Complex and High Dimensional Data.” 2012. Web. 23 Mar 2019.

Vancouver:

Konomi B. Bayesian Spatial Modeling of Complex and High Dimensional Data. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10267.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2012, Texas A&M University

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

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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Xun, Xiaolei. “Statistical Inference in Inverse Problems.” 2012. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Xun, Xiaolei. “Statistical Inference in Inverse Problems.” 2012. Web. 23 Mar 2019.

Vancouver:

Xun X. Statistical Inference in Inverse Problems. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-10874.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2012, Texas A&M University

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

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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Zhang, Lin. “Application of Bayesian Hierarchical Models in Genetic Data Analysis.” 2012. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/148056.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Zhang, Lin. “Application of Bayesian Hierarchical Models in Genetic Data Analysis.” 2012. Web. 23 Mar 2019.

Vancouver:

Zhang L. Application of Bayesian Hierarchical Models in Genetic Data Analysis. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/148056.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2014, Texas A&M University

 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 (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

De, Debkumar. “Essays on Bayesian Time Series and Variable Selection.” 2014. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/152793.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

De, Debkumar. “Essays on Bayesian Time Series and Variable Selection.” 2014. Web. 23 Mar 2019.

Vancouver:

De D. Essays on Bayesian Time Series and Variable Selection. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/152793.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2015, Texas A&M University

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

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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Rahman, Shahina. “Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies.” 2015. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/155719.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Rahman, Shahina. “Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies.” 2015. Web. 23 Mar 2019.

Vancouver:

Rahman S. Efficient Nonparametric and Semiparametric Regression Methods with application in Case-Control Studies. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/155719.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2014, Texas A&M University

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

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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wei, Rubin. “Highly Nonlinear Measurement Error Models in Nutritional Epidemiology.” 2014. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/161236.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wei, Rubin. “Highly Nonlinear Measurement Error Models in Nutritional Epidemiology.” 2014. Web. 23 Mar 2019.

Vancouver:

Wei R. Highly Nonlinear Measurement Error Models in Nutritional Epidemiology. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/161236.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

7. Cho, Jung Jin. On the robustness of clustered sensor networks.

Degree: 2009, Texas A&M University

 Smart devices with multiple on-board sensors, networked through wired or wireless links, are distributed in physical systems and environments. Broad applications of such sensor networks… (more)

Subjects/Keywords: Robustness; Sensor Network; Matroid; Cogirth; Breakdown Point; Robust Estimation

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APA (6th Edition):

Cho, J. J. (2009). On the robustness of clustered sensor networks. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2527

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Cho, Jung Jin. “On the robustness of clustered sensor networks.” 2009. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2527.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Cho, Jung Jin. “On the robustness of clustered sensor networks.” 2009. Web. 23 Mar 2019.

Vancouver:

Cho JJ. On the robustness of clustered sensor networks. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2527.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cho JJ. On the robustness of clustered sensor networks. [Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2527

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

8. Devegowda, Deepak. Streamline Assisted Ensemble Kalman Filter - Formulation and Field Application.

Degree: 2010, Texas A&M University

 The goal of any data assimilation or history matching algorithm is to enable better reservoir management decisions through the construction of reliable reservoir performance models… (more)

Subjects/Keywords: EnKF; Data Assimilation; Covariance Localization; Reservoir Characterization; Streamlines

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APA (6th Edition):

Devegowda, D. (2010). Streamline Assisted Ensemble Kalman Filter - Formulation and Field Application. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-2916

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Devegowda, Deepak. “Streamline Assisted Ensemble Kalman Filter - Formulation and Field Application.” 2010. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-2916.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Devegowda, Deepak. “Streamline Assisted Ensemble Kalman Filter - Formulation and Field Application.” 2010. Web. 23 Mar 2019.

Vancouver:

Devegowda D. Streamline Assisted Ensemble Kalman Filter - Formulation and Field Application. [Internet] [Thesis]. Texas A&M University; 2010. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-2916.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Devegowda D. Streamline Assisted Ensemble Kalman Filter - Formulation and Field Application. [Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-2916

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

9. Ghosh, Souparno. Copula Based Hierarchical Bayesian Models.

Degree: 2010, Texas A&M University

 The main objective of our study is to employ copula methodology to develop Bayesian hierarchical models to study the dependencies exhibited by temporal, spatial and… (more)

Subjects/Keywords: Hierarchical model; Copula; Geostatistics; Extreme value processes

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APA (6th Edition):

Ghosh, S. (2010). Copula Based Hierarchical Bayesian Models. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7160

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ghosh, Souparno. “Copula Based Hierarchical Bayesian Models.” 2010. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7160.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ghosh, Souparno. “Copula Based Hierarchical Bayesian Models.” 2010. Web. 23 Mar 2019.

Vancouver:

Ghosh S. Copula Based Hierarchical Bayesian Models. [Internet] [Thesis]. Texas A&M University; 2010. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7160.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ghosh S. Copula Based Hierarchical Bayesian Models. [Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-7160

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2012, Texas A&M University

 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 (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Talluri, Rajesh. “Bayesian Gaussian Graphical models using sparse selection priors and their mixtures.” 2012. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Talluri, Rajesh. “Bayesian Gaussian Graphical models using sparse selection priors and their mixtures.” 2012. Web. 23 Mar 2019.

Vancouver:

Talluri R. Bayesian Gaussian Graphical models using sparse selection priors and their mixtures. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2010, Texas A&M University

 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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Xia, Haifeng. “Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.” 2010. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Xia, Haifeng. “Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.” 2010. Web. 23 Mar 2019.

Vancouver:

Xia H. Bayesian Hierarchical Model for Combining Two-resolution Metrology Data. [Internet] [Thesis]. Texas A&M University; 2010. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2013, Texas A&M University

 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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hetzler, Adam C. “Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem.” 2013. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/149343.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hetzler, Adam C. “Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem.” 2013. Web. 23 Mar 2019.

Vancouver:

Hetzler AC. Quantification of Uncertainties Due to Opacities in a Laser-Driven Radiative-Shock Problem. [Internet] [Thesis]. Texas A&M University; 2013. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/149343.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2013, Texas A&M University

 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 (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Stripling, Hayes Franklin. “Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations.” 2013. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/151312.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Stripling, Hayes Franklin. “Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations.” 2013. Web. 23 Mar 2019.

Vancouver:

Stripling HF. Adjoint-Based Uncertainty Quantification and Sensitivity Analysis for Reactor Depletion Calculations. [Internet] [Thesis]. Texas A&M University; 2013. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/151312.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2014, Texas A&M University

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

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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sarkar, Abhra. “Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors.” 2014. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/153327.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sarkar, Abhra. “Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors.” 2014. Web. 23 Mar 2019.

Vancouver:

Sarkar A. Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors. [Internet] [Thesis]. Texas A&M University; 2014. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/153327.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2015, Texas A&M University

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

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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Goddard, Scott D. “Restricted Most Powerful Bayesian Tests.” 2015. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/155108.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Goddard, Scott D. “Restricted Most Powerful Bayesian Tests.” 2015. Web. 23 Mar 2019.

Vancouver:

Goddard SD. Restricted Most Powerful Bayesian Tests. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/155108.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

16. 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

 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 (6th 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 (16th 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 March 23, 2019. http://hdl.handle.net/1969.1/157993.

MLA Handbook (7th Edition):

Alahmadi, Hasan Ali H. “A Model for Optimizing Energy Investments and Policy Under Uncertainty with Application to Saudi Arabia.” 2016. Web. 23 Mar 2019.

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 2019 Mar 23]. 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

17. Maity, Arnab. Efficient inference in general semiparametric regression models.

Degree: 2009, Texas A&M University

 Semiparametric regression has become very popular in the field of Statistics over the years. While on one hand more and more sophisticated models are being… (more)

Subjects/Keywords: Nonparametric/Semiparametric Regression; Kernel Method; Measurement Error; Semiparametric Efficiency; Repeated Measures

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

APA (6th Edition):

Maity, A. (2009). Efficient inference in general semiparametric regression models. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-3075

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Maity, Arnab. “Efficient inference in general semiparametric regression models.” 2009. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-3075.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Maity, Arnab. “Efficient inference in general semiparametric regression models.” 2009. Web. 23 Mar 2019.

Vancouver:

Maity A. Efficient inference in general semiparametric regression models. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-3075.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Maity A. Efficient inference in general semiparametric regression models. [Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-3075

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2009, Texas A&M University

 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

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

APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Wang, Xiaohui. “Bayesian classification and survival analysis with curve predictors.” 2009. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-1205.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Wang, Xiaohui. “Bayesian classification and survival analysis with curve predictors.” 2009. Web. 23 Mar 2019.

Vancouver:

Wang X. Bayesian classification and survival analysis with curve predictors. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1205.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2011, Texas A&M University

 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 (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Stripling, Hayes Franklin. “The Method of Manufactured Universes for Testing Uncertainty Quantification Methods.” 2011. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8986.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Stripling, Hayes Franklin. “The Method of Manufactured Universes for Testing Uncertainty Quantification Methods.” 2011. Web. 23 Mar 2019.

Vancouver:

Stripling HF. The Method of Manufactured Universes for Testing Uncertainty Quantification Methods. [Internet] [Thesis]. Texas A&M University; 2011. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8986.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2006, Texas A&M University

 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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chowdhury, Nilanjan Dutta. “Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines.” 2006. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/3302.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chowdhury, Nilanjan Dutta. “Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines.” 2006. Web. 23 Mar 2019.

Vancouver:

Chowdhury ND. Computational evaluation of a novel approach to process planning for circuit card assembly on dual head placement machines. [Internet] [Thesis]. Texas A&M University; 2006. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/3302.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2005, Texas A&M University

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

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

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

APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Ryu, Duchwan. “Regression analysis with longitudinal measurements.” 2005. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/2398.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Ryu, Duchwan. “Regression analysis with longitudinal measurements.” 2005. Web. 23 Mar 2019.

Vancouver:

Ryu D. Regression analysis with longitudinal measurements. [Internet] [Thesis]. Texas A&M University; 2005. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/2398.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2016, Texas A&M University

 Uncertainty quanti?cation 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 (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Humbird, Kelli Denise. “Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion.” 2016. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/157147.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Humbird, Kelli Denise. “Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion.” 2016. Web. 23 Mar 2019.

Vancouver:

Humbird KD. Adjoint-Based Sensitivity Analysis for Flux-Limited Diffusion. [Internet] [Thesis]. Texas A&M University; 2016. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/157147.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2012, Texas A&M University

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

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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Dhavala, Soma Sekhar. “Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression.” 2012. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Dhavala, Soma Sekhar. “Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression.” 2012. Web. 23 Mar 2019.

Vancouver:

Dhavala SS. Bayesian Semiparametric Models for Heterogeneous Cross-platform Differential Gene Expression. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-12-8659.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2012, Texas A&M University

 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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mondal, Anirban. “Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems.” 2012. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mondal, Anirban. “Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems.” 2012. Web. 23 Mar 2019.

Vancouver:

Mondal A. Bayesian Uncertainty Quantification for Large Scale Spatial Inverse Problems. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9905.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2005, Texas A&M University

 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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lee, Kyeong Eun. “Bayesian models for DNA microarray data analysis.” 2005. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/2465.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lee, Kyeong Eun. “Bayesian models for DNA microarray data analysis.” 2005. Web. 23 Mar 2019.

Vancouver:

Lee KE. Bayesian models for DNA microarray data analysis. [Internet] [Thesis]. Texas A&M University; 2005. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/2465.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2011, Texas A&M University

 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 (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hartman, Brian Matthew. “Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion.” 2011. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8294.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hartman, Brian Matthew. “Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion.” 2011. Web. 23 Mar 2019.

Vancouver:

Hartman BM. Bayesian Hierarchical, Semiparametric, and Nonparametric Methods for International New Product Di ffusion. [Internet] [Thesis]. Texas A&M University; 2011. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2010-08-8294.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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

Degree: 2011, Texas A&M University

 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

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APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Shrivastava, Abhishek Kumar. “Listing Unique Fractional Factorial Designs.” 2011. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7345.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Shrivastava, Abhishek Kumar. “Listing Unique Fractional Factorial Designs.” 2011. Web. 23 Mar 2019.

Vancouver:

Shrivastava AK. Listing Unique Fractional Factorial Designs. [Internet] [Thesis]. Texas A&M University; 2011. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7345.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2005, Texas A&M University

 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

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

APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lee, Ho-Jin. “Functional data analysis: classification and regression.” 2005. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/2805.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lee, Ho-Jin. “Functional data analysis: classification and regression.” 2005. Web. 23 Mar 2019.

Vancouver:

Lee H. Functional data analysis: classification and regression. [Internet] [Thesis]. Texas A&M University; 2005. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/2805.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2006, Texas A&M University

 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

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

APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Luo, Wen. “Reliability characterization and prediction of high k dielectric thin film.” 2006. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/3225.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Luo, Wen. “Reliability characterization and prediction of high k dielectric thin film.” 2006. Web. 23 Mar 2019.

Vancouver:

Luo W. Reliability characterization and prediction of high k dielectric thin film. [Internet] [Thesis]. Texas A&M University; 2006. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/3225.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Texas A&M University

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

Degree: 2006, Texas A&M University

 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

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

APA (6th Edition):

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Chang, Ilsung. “Bayesian inference on mixture models and their applications.” 2006. Thesis, Texas A&M University. Accessed March 23, 2019. http://hdl.handle.net/1969.1/3990.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Chang, Ilsung. “Bayesian inference on mixture models and their applications.” 2006. Web. 23 Mar 2019.

Vancouver:

Chang I. Bayesian inference on mixture models and their applications. [Internet] [Thesis]. Texas A&M University; 2006. [cited 2019 Mar 23]. Available from: http://hdl.handle.net/1969.1/3990.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

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

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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