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You searched for +publisher:"University of Texas – Austin" +contributor:("Scott, James"). Showing records 1 – 18 of 18 total matches.

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University of Texas – Austin

1. Buddhavarapu, Prasad Naga Venkata Siva Rama. Modeling unobserved heterogeneity of spatially correlated count data using finite-mixture random parameters.

Degree: MSin Statistics, Statistics, 2015, University of Texas – Austin

 The main goal of this research is to propose a specification to model the unobserved heterogeneity in count outcomes. A negative binomial likelihood is utilized… (more)

Subjects/Keywords: Finite-mixture models; Negative-binomial; Unobserved heterogeneity; Bayesian inference; Data-augmentation

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APA (6th Edition):

Buddhavarapu, P. N. V. S. R. (2015). Modeling unobserved heterogeneity of spatially correlated count data using finite-mixture random parameters. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32501

Chicago Manual of Style (16th Edition):

Buddhavarapu, Prasad Naga Venkata Siva Rama. “Modeling unobserved heterogeneity of spatially correlated count data using finite-mixture random parameters.” 2015. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/32501.

MLA Handbook (7th Edition):

Buddhavarapu, Prasad Naga Venkata Siva Rama. “Modeling unobserved heterogeneity of spatially correlated count data using finite-mixture random parameters.” 2015. Web. 28 Feb 2021.

Vancouver:

Buddhavarapu PNVSR. Modeling unobserved heterogeneity of spatially correlated count data using finite-mixture random parameters. [Internet] [Masters thesis]. University of Texas – Austin; 2015. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/32501.

Council of Science Editors:

Buddhavarapu PNVSR. Modeling unobserved heterogeneity of spatially correlated count data using finite-mixture random parameters. [Masters Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32501


University of Texas – Austin

2. Gillett, Carlos Townes. A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions.

Degree: MSin Statistics, Statistics, 2015, University of Texas – Austin

 This report compares the convergence behavior of the Metropolis-Hastings and an alternative Markov Chain Monte Carlo sampling algorithm targeting unnormalized, discrete distributions with countably infinite… (more)

Subjects/Keywords: Metropolis-Hastings; Bayesian inference; Unnormalized probabilities

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APA (6th Edition):

Gillett, C. T. (2015). A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32494

Chicago Manual of Style (16th Edition):

Gillett, Carlos Townes. “A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions.” 2015. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/32494.

MLA Handbook (7th Edition):

Gillett, Carlos Townes. “A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions.” 2015. Web. 28 Feb 2021.

Vancouver:

Gillett CT. A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions. [Internet] [Masters thesis]. University of Texas – Austin; 2015. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/32494.

Council of Science Editors:

Gillett CT. A comparison of two Markov Chain Monte Carlo methods for sampling from unnormalized discrete distributions. [Masters Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32494

3. Madrid Padilla, Oscar Hernan. Constrained estimation via the fused lasso and some generalizations.

Degree: PhD, Statistics, 2017, University of Texas – Austin

 This dissertation studies structurally constrained statistical estimators. Two entwined main themes are developed: computationally efficient algorithms, and strong statistical guarantees of estimators across a wide… (more)

Subjects/Keywords: Fused lasso; Penalized likelihood.

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APA (6th Edition):

Madrid Padilla, O. H. (2017). Constrained estimation via the fused lasso and some generalizations. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63067

Chicago Manual of Style (16th Edition):

Madrid Padilla, Oscar Hernan. “Constrained estimation via the fused lasso and some generalizations.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/63067.

MLA Handbook (7th Edition):

Madrid Padilla, Oscar Hernan. “Constrained estimation via the fused lasso and some generalizations.” 2017. Web. 28 Feb 2021.

Vancouver:

Madrid Padilla OH. Constrained estimation via the fused lasso and some generalizations. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/63067.

Council of Science Editors:

Madrid Padilla OH. Constrained estimation via the fused lasso and some generalizations. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/63067


University of Texas – Austin

4. Garrette, Daniel Hunter. Inducing grammars from linguistic universals and realistic amounts of supervision.

Degree: PhD, Artificial intelligence, 2015, University of Texas – Austin

 The best performing NLP models to date are learned from large volumes of manually-annotated data. For tasks like part-of-speech tagging and grammatical parsing, high performance… (more)

Subjects/Keywords: Computer science; Artificial intelligence; Natural language processing; Machine learning; Bayesian statistics; Grammar induction; Parsing; Computational linguistics

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APA (6th Edition):

Garrette, D. H. (2015). Inducing grammars from linguistic universals and realistic amounts of supervision. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/44478

Chicago Manual of Style (16th Edition):

Garrette, Daniel Hunter. “Inducing grammars from linguistic universals and realistic amounts of supervision.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/44478.

MLA Handbook (7th Edition):

Garrette, Daniel Hunter. “Inducing grammars from linguistic universals and realistic amounts of supervision.” 2015. Web. 28 Feb 2021.

Vancouver:

Garrette DH. Inducing grammars from linguistic universals and realistic amounts of supervision. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/44478.

Council of Science Editors:

Garrette DH. Inducing grammars from linguistic universals and realistic amounts of supervision. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/44478


University of Texas – Austin

5. -2304-7384. Improving surveillance and prediction of emerging and re-emerging infectious diseases.

Degree: PhD, Cell and Molecular Biology, 2020, University of Texas – Austin

 Infectious diseases are emerging at an unprecedent rate in recent years, such as the flu pandemic initialized from Mexico in 2009, the 2014 Ebola epidemic… (more)

Subjects/Keywords: Emerging infectious diseases; Re-emerging infectious diseases; Surveillance; Early detection; Prediction; Mathematical models; Statistical models

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APA (6th Edition):

-2304-7384. (2020). Improving surveillance and prediction of emerging and re-emerging infectious diseases. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/7632

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Chicago Manual of Style (16th Edition):

-2304-7384. “Improving surveillance and prediction of emerging and re-emerging infectious diseases.” 2020. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://dx.doi.org/10.26153/tsw/7632.

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Author name may be incomplete

MLA Handbook (7th Edition):

-2304-7384. “Improving surveillance and prediction of emerging and re-emerging infectious diseases.” 2020. Web. 28 Feb 2021.

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Author name may be incomplete

Vancouver:

-2304-7384. Improving surveillance and prediction of emerging and re-emerging infectious diseases. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2020. [cited 2021 Feb 28]. Available from: http://dx.doi.org/10.26153/tsw/7632.

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

Council of Science Editors:

-2304-7384. Improving surveillance and prediction of emerging and re-emerging infectious diseases. [Doctoral Dissertation]. University of Texas – Austin; 2020. Available from: http://dx.doi.org/10.26153/tsw/7632

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Author name may be incomplete


University of Texas – Austin

6. -9322-9685. Discovering latent structures in syntax trees and mixed-type data.

Degree: PhD, Operations Research and Industrial Engineering, 2016, University of Texas – Austin

 Gibbs sampling is a widely applied algorithm to estimate parameters in statistical models. This thesis uses Gibbs sampling to resolve practical problems, especially on natural… (more)

Subjects/Keywords: Gibbs sampling; Natural language processing; Bayesian statistics; Factor analysis; Syntax trees parsing

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APA (6th Edition):

-9322-9685. (2016). Discovering latent structures in syntax trees and mixed-type data. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68368

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Chicago Manual of Style (16th Edition):

-9322-9685. “Discovering latent structures in syntax trees and mixed-type data.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/68368.

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Author name may be incomplete

MLA Handbook (7th Edition):

-9322-9685. “Discovering latent structures in syntax trees and mixed-type data.” 2016. Web. 28 Feb 2021.

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Author name may be incomplete

Vancouver:

-9322-9685. Discovering latent structures in syntax trees and mixed-type data. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/68368.

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

Council of Science Editors:

-9322-9685. Discovering latent structures in syntax trees and mixed-type data. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/68368

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

7. -9309-5664. Regularization in econometrics and finance.

Degree: PhD, Statistics, 2018, University of Texas – Austin

 This dissertation develops regularization methods for use in finance and econometrics problems. The key methodology introduced is utility-based selection (UBS)  – a procedure for inducing… (more)

Subjects/Keywords: Utility-based posterior summarization; Asset pricing; Cross-section of returns

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th Edition):

-9309-5664. (2018). Regularization in econometrics and finance. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/65998

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Chicago Manual of Style (16th Edition):

-9309-5664. “Regularization in econometrics and finance.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/65998.

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Author name may be incomplete

MLA Handbook (7th Edition):

-9309-5664. “Regularization in econometrics and finance.” 2018. Web. 28 Feb 2021.

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

Vancouver:

-9309-5664. Regularization in econometrics and finance. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/65998.

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

Council of Science Editors:

-9309-5664. Regularization in econometrics and finance. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/65998

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Author name may be incomplete


University of Texas – Austin

8. Zhang, Michael Minyi. Scalable inference for Bayesian non-parametrics.

Degree: PhD, Statistics, 2018, University of Texas – Austin

 Bayesian non-parametric models, despite their theoretical elegance, face a serious computational burden that prevents their use in serious "big data'' scenarios. Furthermore, we cannot expect… (more)

Subjects/Keywords: Bayesian non-parametrics; Scalable inference; Machine learning

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APA (6th Edition):

Zhang, M. M. (2018). Scalable inference for Bayesian non-parametrics. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/65734

Chicago Manual of Style (16th Edition):

Zhang, Michael Minyi. “Scalable inference for Bayesian non-parametrics.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/65734.

MLA Handbook (7th Edition):

Zhang, Michael Minyi. “Scalable inference for Bayesian non-parametrics.” 2018. Web. 28 Feb 2021.

Vancouver:

Zhang MM. Scalable inference for Bayesian non-parametrics. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/65734.

Council of Science Editors:

Zhang MM. Scalable inference for Bayesian non-parametrics. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/65734

9. Liu, Zhuping. Push and pull : targeting and couponing in mobile marketing.

Degree: PhD, Marketing, 2017, University of Texas – Austin

 The prevalence of mobile marketing practices has profoundly changed the way consumers shop. Consumers are increasingly shifting to mobile coupons to enhance their shopping experiences.… (more)

Subjects/Keywords: Mobile marketing; Targeting; Consumer search

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APA (6th Edition):

Liu, Z. (2017). Push and pull : targeting and couponing in mobile marketing. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62095

Chicago Manual of Style (16th Edition):

Liu, Zhuping. “Push and pull : targeting and couponing in mobile marketing.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/62095.

MLA Handbook (7th Edition):

Liu, Zhuping. “Push and pull : targeting and couponing in mobile marketing.” 2017. Web. 28 Feb 2021.

Vancouver:

Liu Z. Push and pull : targeting and couponing in mobile marketing. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/62095.

Council of Science Editors:

Liu Z. Push and pull : targeting and couponing in mobile marketing. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62095


University of Texas – Austin

10. Buddhavarapu, Prasad Naga Venkata Siva Rama. On Bayesian estimation of spatial and dynamic count models using data augmentation techniques : application to road safety management.

Degree: PhD, Civil engineering, 2015, University of Texas – Austin

 Over the past several years, roadway safety management has evolved into data-driven or evidence-based science. The corner stone of a data-driven roadway safety management is… (more)

Subjects/Keywords: Bayesian statistics; Polya gamma data augmentation; Road safety management; Pavements; Markov chain monte carlo simulation

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APA (6th Edition):

Buddhavarapu, P. N. V. S. R. (2015). On Bayesian estimation of spatial and dynamic count models using data augmentation techniques : application to road safety management. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32525

Chicago Manual of Style (16th Edition):

Buddhavarapu, Prasad Naga Venkata Siva Rama. “On Bayesian estimation of spatial and dynamic count models using data augmentation techniques : application to road safety management.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/32525.

MLA Handbook (7th Edition):

Buddhavarapu, Prasad Naga Venkata Siva Rama. “On Bayesian estimation of spatial and dynamic count models using data augmentation techniques : application to road safety management.” 2015. Web. 28 Feb 2021.

Vancouver:

Buddhavarapu PNVSR. On Bayesian estimation of spatial and dynamic count models using data augmentation techniques : application to road safety management. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/32525.

Council of Science Editors:

Buddhavarapu PNVSR. On Bayesian estimation of spatial and dynamic count models using data augmentation techniques : application to road safety management. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32525

11. Zhang, Wenjie, active 2013. The relationships between crime rate and income inequality : evidence from China.

Degree: MSin Statistics, Statistics, 2013, University of Texas – Austin

 The main purpose of this study is to determine if a Bayesian approach can better capture and provide reasonable predictions for the complex linkage between… (more)

Subjects/Keywords: Crime rate; Inequality; Classical inference; Bayesian inference

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APA (6th Edition):

Zhang, Wenjie, a. 2. (2013). The relationships between crime rate and income inequality : evidence from China. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/22551

Chicago Manual of Style (16th Edition):

Zhang, Wenjie, active 2013. “The relationships between crime rate and income inequality : evidence from China.” 2013. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/22551.

MLA Handbook (7th Edition):

Zhang, Wenjie, active 2013. “The relationships between crime rate and income inequality : evidence from China.” 2013. Web. 28 Feb 2021.

Vancouver:

Zhang, Wenjie a2. The relationships between crime rate and income inequality : evidence from China. [Internet] [Masters thesis]. University of Texas – Austin; 2013. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/22551.

Council of Science Editors:

Zhang, Wenjie a2. The relationships between crime rate and income inequality : evidence from China. [Masters Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/22551

12. Lakin, Richard Thomas. Bayesian hierarchical parametric survival analysis for NBA career longevity.

Degree: MSin Statistics, Statistics, 2012, University of Texas – Austin

 In evaluating a prospective NBA player, one might consider past performance in the player’s previous years of competition. In doing so, a general manager may… (more)

Subjects/Keywords: Survival; Bayesian; Hierarchical; NBA; Sports

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APA (6th Edition):

Lakin, R. T. (2012). Bayesian hierarchical parametric survival analysis for NBA career longevity. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5631

Chicago Manual of Style (16th Edition):

Lakin, Richard Thomas. “Bayesian hierarchical parametric survival analysis for NBA career longevity.” 2012. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/ETD-UT-2012-05-5631.

MLA Handbook (7th Edition):

Lakin, Richard Thomas. “Bayesian hierarchical parametric survival analysis for NBA career longevity.” 2012. Web. 28 Feb 2021.

Vancouver:

Lakin RT. Bayesian hierarchical parametric survival analysis for NBA career longevity. [Internet] [Masters thesis]. University of Texas – Austin; 2012. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5631.

Council of Science Editors:

Lakin RT. Bayesian hierarchical parametric survival analysis for NBA career longevity. [Masters Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5631

13. -1538-3599. Spatial pricing empirical evaluation of ride-sourcing trips using the graph-fussed lasso for total variation denoising.

Degree: MSin Statistics, Statistics, 2019, University of Texas – Austin

 This study explores the spatial pricing discrimination of ride-sourcing trips using empirical data. We use information from more than 1.1 million rides in Austin, Texas,… (more)

Subjects/Keywords: Ride-sourcing; Ride-sharing; Spatial pricing; Fused lasso; Total variation denoising; Graph smoothing

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APA (6th Edition):

-1538-3599. (2019). Spatial pricing empirical evaluation of ride-sourcing trips using the graph-fussed lasso for total variation denoising. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/72845

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Chicago Manual of Style (16th Edition):

-1538-3599. “Spatial pricing empirical evaluation of ride-sourcing trips using the graph-fussed lasso for total variation denoising.” 2019. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/72845.

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Author name may be incomplete

MLA Handbook (7th Edition):

-1538-3599. “Spatial pricing empirical evaluation of ride-sourcing trips using the graph-fussed lasso for total variation denoising.” 2019. Web. 28 Feb 2021.

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

Vancouver:

-1538-3599. Spatial pricing empirical evaluation of ride-sourcing trips using the graph-fussed lasso for total variation denoising. [Internet] [Masters thesis]. University of Texas – Austin; 2019. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/72845.

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Author name may be incomplete

Council of Science Editors:

-1538-3599. Spatial pricing empirical evaluation of ride-sourcing trips using the graph-fussed lasso for total variation denoising. [Masters Thesis]. University of Texas – Austin; 2019. Available from: http://hdl.handle.net/2152/72845

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14. Chancellor, Courtney Marie. Predicting emergency department events due to asthma : results from the BRFSS Asthma Call Back Survey 2006-2009.

Degree: MSin Computational Science, Engineering, and Mathematics, Computational Science, Engineering, and Mathematics, 2012, University of Texas – Austin

 The identification of asthma patients most at risk of experiencing an emergency department event is an important step toward lessening public health burdens in the… (more)

Subjects/Keywords: Asthma; Predictive modeling; rpart; Regression trees

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APA (6th Edition):

Chancellor, C. M. (2012). Predicting emergency department events due to asthma : results from the BRFSS Asthma Call Back Survey 2006-2009. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5551

Chicago Manual of Style (16th Edition):

Chancellor, Courtney Marie. “Predicting emergency department events due to asthma : results from the BRFSS Asthma Call Back Survey 2006-2009.” 2012. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/ETD-UT-2012-05-5551.

MLA Handbook (7th Edition):

Chancellor, Courtney Marie. “Predicting emergency department events due to asthma : results from the BRFSS Asthma Call Back Survey 2006-2009.” 2012. Web. 28 Feb 2021.

Vancouver:

Chancellor CM. Predicting emergency department events due to asthma : results from the BRFSS Asthma Call Back Survey 2006-2009. [Internet] [Masters thesis]. University of Texas – Austin; 2012. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5551.

Council of Science Editors:

Chancellor CM. Predicting emergency department events due to asthma : results from the BRFSS Asthma Call Back Survey 2006-2009. [Masters Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5551

15. -8326-9643. Spatial interpolation with Gaussian processes and spatially varying regression coefficients.

Degree: MSin Statistics, Statistics, 2015, University of Texas – Austin

 Linear regression is undoubtedly one of the most widely used statistical techniques, however because it assumes independent observations it can miss important features of a… (more)

Subjects/Keywords: Spatial statistics; Gaussian process; Spatial interpolation; Spatially varying coefficients

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APA (6th Edition):

-8326-9643. (2015). Spatial interpolation with Gaussian processes and spatially varying regression coefficients. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32508

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Chicago Manual of Style (16th Edition):

-8326-9643. “Spatial interpolation with Gaussian processes and spatially varying regression coefficients.” 2015. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/32508.

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MLA Handbook (7th Edition):

-8326-9643. “Spatial interpolation with Gaussian processes and spatially varying regression coefficients.” 2015. Web. 28 Feb 2021.

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

Vancouver:

-8326-9643. Spatial interpolation with Gaussian processes and spatially varying regression coefficients. [Internet] [Masters thesis]. University of Texas – Austin; 2015. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/32508.

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Author name may be incomplete

Council of Science Editors:

-8326-9643. Spatial interpolation with Gaussian processes and spatially varying regression coefficients. [Masters Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32508

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16. Martin, Stephen Fredrick. Applying Classification and Regression Trees to manage financial risk.

Degree: MSin Statistics, Statistics, 2012, University of Texas – Austin

 This goal of this project is to develop a set of business rules to mitigate risk related to a specific financial decision within the prepaid… (more)

Subjects/Keywords: CART; Classification and Regression Trees; Breiman; Risk; Prepaid; Debit cards; Rollback; R; RPART; Cross validation

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

APA (6th Edition):

Martin, S. F. (2012). Applying Classification and Regression Trees to manage financial risk. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/ETD-UT-2012-05-5428

Chicago Manual of Style (16th Edition):

Martin, Stephen Fredrick. “Applying Classification and Regression Trees to manage financial risk.” 2012. Masters Thesis, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/ETD-UT-2012-05-5428.

MLA Handbook (7th Edition):

Martin, Stephen Fredrick. “Applying Classification and Regression Trees to manage financial risk.” 2012. Web. 28 Feb 2021.

Vancouver:

Martin SF. Applying Classification and Regression Trees to manage financial risk. [Internet] [Masters thesis]. University of Texas – Austin; 2012. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5428.

Council of Science Editors:

Martin SF. Applying Classification and Regression Trees to manage financial risk. [Masters Thesis]. University of Texas – Austin; 2012. Available from: http://hdl.handle.net/2152/ETD-UT-2012-05-5428

17. -5294-4228. Scalable smoothing algorithms for massive graph-structured data.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

 Probabilistically modeling noisy data is a crucial step in virtually all scientific experiments and engineering pipelines. Recent years have seen the rise of several high-throughput… (more)

Subjects/Keywords: Smoothing; Algorithms; False discovery rate; Spatial smoothing; Total variation; Trend filtering

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

APA (6th Edition):

-5294-4228. (2017). Scalable smoothing algorithms for massive graph-structured data. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/61823

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

Chicago Manual of Style (16th Edition):

-5294-4228. “Scalable smoothing algorithms for massive graph-structured data.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/61823.

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

MLA Handbook (7th Edition):

-5294-4228. “Scalable smoothing algorithms for massive graph-structured data.” 2017. Web. 28 Feb 2021.

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

Vancouver:

-5294-4228. Scalable smoothing algorithms for massive graph-structured data. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/61823.

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

Council of Science Editors:

-5294-4228. Scalable smoothing algorithms for massive graph-structured data. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/61823

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

18. Jo, Jason. Structured low complexity data mining.

Degree: PhD, Mathematics, 2015, University of Texas – Austin

 Due to the rapidly increasing dimensionality of modern datasets many classical approximation algorithms have run into severe computational bottlenecks. This has often been referred to… (more)

Subjects/Keywords: Greedy sparse approximation; Weighted matrix completion

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

APA (6th Edition):

Jo, J. (2015). Structured low complexity data mining. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/31510

Chicago Manual of Style (16th Edition):

Jo, Jason. “Structured low complexity data mining.” 2015. Doctoral Dissertation, University of Texas – Austin. Accessed February 28, 2021. http://hdl.handle.net/2152/31510.

MLA Handbook (7th Edition):

Jo, Jason. “Structured low complexity data mining.” 2015. Web. 28 Feb 2021.

Vancouver:

Jo J. Structured low complexity data mining. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2015. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2152/31510.

Council of Science Editors:

Jo J. Structured low complexity data mining. [Doctoral Dissertation]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/31510

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