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Virginia Tech

1.
Krometis, Justin August.
A *Bayesian* Approach to Estimating Background Flows from a Passive Scalar.

Degree: PhD, Mathematics, 2018, Virginia Tech

URL: http://hdl.handle.net/10919/83783

► We consider the statistical inverse problem of estimating a background flow field (e.g., of air or water) from the partial and noisy observation of a…
(more)

Subjects/Keywords: Bayesian Statistical Inversion; Bayesian Consistency; Markov Chain Monte Carlo (MCMC); Passive Scalars; Fluid Turbulence

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APA (6^{th} Edition):

Krometis, J. A. (2018). A Bayesian Approach to Estimating Background Flows from a Passive Scalar. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83783

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

Krometis, Justin August. “A Bayesian Approach to Estimating Background Flows from a Passive Scalar.” 2018. Doctoral Dissertation, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/83783.

MLA Handbook (7^{th} Edition):

Krometis, Justin August. “A Bayesian Approach to Estimating Background Flows from a Passive Scalar.” 2018. Web. 22 Sep 2019.

Vancouver:

Krometis JA. A Bayesian Approach to Estimating Background Flows from a Passive Scalar. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/83783.

Council of Science Editors:

Krometis JA. A Bayesian Approach to Estimating Background Flows from a Passive Scalar. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83783

2.
Grollemund, Paul-Marie.
Régression linéaire bayésienne sur données fonctionnelles : Functional *Bayesian* linear regression.

Degree: Docteur es, Biostatistique, 2017, Montpellier

URL: http://www.theses.fr/2017MONTS045

►

Un outil fondamental en statistique est le modèle de régression linéaire. Lorsqu'une des covariables est une fonction, on fait face à un problème de statistique… (more)

Subjects/Keywords: Régression linéaire fonctionnelle; Bayésien; Parcimonie; Consistance; Elicitation; Functional linear regression; Bayesian; Sparsity; Posterior consistency; Elicitation

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APA (6^{th} Edition):

Grollemund, P. (2017). Régression linéaire bayésienne sur données fonctionnelles : Functional Bayesian linear regression. (Doctoral Dissertation). Montpellier. Retrieved from http://www.theses.fr/2017MONTS045

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

Grollemund, Paul-Marie. “Régression linéaire bayésienne sur données fonctionnelles : Functional Bayesian linear regression.” 2017. Doctoral Dissertation, Montpellier. Accessed September 22, 2019. http://www.theses.fr/2017MONTS045.

MLA Handbook (7^{th} Edition):

Grollemund, Paul-Marie. “Régression linéaire bayésienne sur données fonctionnelles : Functional Bayesian linear regression.” 2017. Web. 22 Sep 2019.

Vancouver:

Grollemund P. Régression linéaire bayésienne sur données fonctionnelles : Functional Bayesian linear regression. [Internet] [Doctoral dissertation]. Montpellier; 2017. [cited 2019 Sep 22]. Available from: http://www.theses.fr/2017MONTS045.

Council of Science Editors:

Grollemund P. Régression linéaire bayésienne sur données fonctionnelles : Functional Bayesian linear regression. [Doctoral Dissertation]. Montpellier; 2017. Available from: http://www.theses.fr/2017MONTS045

North Carolina State University

3. Krachey, Elizabeth Catherine. Variations on the Accelerated Failure Time Model: Mixture Distributions, Cure Rates, and Di fferent Censoring Scenarios.

Degree: PhD, Statistics, 2009, North Carolina State University

URL: http://www.lib.ncsu.edu/resolver/1840.16/3619

► The accelerated failure time (AFT) model is a popular model for time-to-event data. It provides a useful alternative when the proportional hazards assumption is in…
(more)

Subjects/Keywords: Markov chain Monte Carlo method; Long-term survival; Interval-censoring; Bayesian; Posterior consistency; Mixture density

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APA (6^{th} Edition):

Krachey, E. C. (2009). Variations on the Accelerated Failure Time Model: Mixture Distributions, Cure Rates, and Di fferent Censoring Scenarios. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/3619

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

Krachey, Elizabeth Catherine. “Variations on the Accelerated Failure Time Model: Mixture Distributions, Cure Rates, and Di fferent Censoring Scenarios.” 2009. Doctoral Dissertation, North Carolina State University. Accessed September 22, 2019. http://www.lib.ncsu.edu/resolver/1840.16/3619.

MLA Handbook (7^{th} Edition):

Krachey, Elizabeth Catherine. “Variations on the Accelerated Failure Time Model: Mixture Distributions, Cure Rates, and Di fferent Censoring Scenarios.” 2009. Web. 22 Sep 2019.

Vancouver:

Krachey EC. Variations on the Accelerated Failure Time Model: Mixture Distributions, Cure Rates, and Di fferent Censoring Scenarios. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Sep 22]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/3619.

Council of Science Editors:

Krachey EC. Variations on the Accelerated Failure Time Model: Mixture Distributions, Cure Rates, and Di fferent Censoring Scenarios. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/3619

University of Florida

4.
Xiang, Ruoxuan.
* Consistency* of High Dimensional

Degree: PhD, Statistics, 2016, University of Florida

URL: http://ufdc.ufl.edu/UFE0050143

► In the first project, we examine Bayes factor *consistency* in the context of *Bayesian* variable selection for normal linear regression models. We take a hierarchical…
(more)

Subjects/Keywords: Approximation; Bayes theorem; Covariance; Matrices; Modeling; Parametric models; Statistical estimation; Statistical models; Statistics; Vertices; bayesian – consistency

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

APA (6^{th} Edition):

Xiang, R. (2016). Consistency of High Dimensional Bayesian Models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0050143

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

Xiang, Ruoxuan. “Consistency of High Dimensional Bayesian Models.” 2016. Doctoral Dissertation, University of Florida. Accessed September 22, 2019. http://ufdc.ufl.edu/UFE0050143.

MLA Handbook (7^{th} Edition):

Xiang, Ruoxuan. “Consistency of High Dimensional Bayesian Models.” 2016. Web. 22 Sep 2019.

Vancouver:

Xiang R. Consistency of High Dimensional Bayesian Models. [Internet] [Doctoral dissertation]. University of Florida; 2016. [cited 2019 Sep 22]. Available from: http://ufdc.ufl.edu/UFE0050143.

Council of Science Editors:

Xiang R. Consistency of High Dimensional Bayesian Models. [Doctoral Dissertation]. University of Florida; 2016. Available from: http://ufdc.ufl.edu/UFE0050143

University of Pennsylvania

5.
Luu, Long.
Self-*Consistency* In Sequential Decision-Making.

Degree: 2018, University of Pennsylvania

URL: https://repository.upenn.edu/edissertations/3152

► Human decisions are rarely made in isolation. We typically have to make a sequence of decisions to reach a goal. Studies in economics and cognitive…
(more)

Subjects/Keywords: Bayesian decision theory; Decision-making; Perception; Psychophysics; Self-consistency; Sequential judgment; Neuroscience and Neurobiology; Psychology; Social and Behavioral Sciences

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

APA (6^{th} Edition):

Luu, L. (2018). Self-Consistency In Sequential Decision-Making. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/3152

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

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

Luu, Long. “Self-Consistency In Sequential Decision-Making.” 2018. Thesis, University of Pennsylvania. Accessed September 22, 2019. https://repository.upenn.edu/edissertations/3152.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Luu, Long. “Self-Consistency In Sequential Decision-Making.” 2018. Web. 22 Sep 2019.

Vancouver:

Luu L. Self-Consistency In Sequential Decision-Making. [Internet] [Thesis]. University of Pennsylvania; 2018. [cited 2019 Sep 22]. Available from: https://repository.upenn.edu/edissertations/3152.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Luu L. Self-Consistency In Sequential Decision-Making. [Thesis]. University of Pennsylvania; 2018. Available from: https://repository.upenn.edu/edissertations/3152

Not specified: Masters Thesis or Doctoral Dissertation

6.
Ho, Chi-San.
Mixtures of triangular densities with applications to *Bayesian* mode regressions.

Degree: PhD, Information, Risk, and Operations Management, 2014, University of Texas – Austin

URL: http://hdl.handle.net/2152/26077

► The main focus of this thesis is to develop full parametric and semiparametric *Bayesian* inference for data arising from triangular distributions. A natural consequence of…
(more)

Subjects/Keywords: Bayesian inference; Consistency; Convex densities; Triangular distributions

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

APA (6^{th} Edition):

Ho, C. (2014). Mixtures of triangular densities with applications to Bayesian mode regressions. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/26077

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

Ho, Chi-San. “Mixtures of triangular densities with applications to Bayesian mode regressions.” 2014. Doctoral Dissertation, University of Texas – Austin. Accessed September 22, 2019. http://hdl.handle.net/2152/26077.

MLA Handbook (7^{th} Edition):

Ho, Chi-San. “Mixtures of triangular densities with applications to Bayesian mode regressions.” 2014. Web. 22 Sep 2019.

Vancouver:

Ho C. Mixtures of triangular densities with applications to Bayesian mode regressions. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2014. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/2152/26077.

Council of Science Editors:

Ho C. Mixtures of triangular densities with applications to Bayesian mode regressions. [Doctoral Dissertation]. University of Texas – Austin; 2014. Available from: http://hdl.handle.net/2152/26077

7.
Chang, Chao.
Nonparametric *Bayesian* Quantile Regression via Dirichlet Process Mixture Models.

Degree: PhD, Mathematics, 2015, Washington University in St. Louis

URL: https://openscholarship.wustl.edu/art_sci_etds/458

► We propose new nonparametric *Bayesian* approaches to quantile regression using Dirichlet process mixture (DPM) models. All the existing quantile regression methods based on DPMs…
(more)

Subjects/Keywords: Dirichlet Process Mixture, Nonparametric Bayesian, Posterior Consistency, Quantile Regression; Mathematics

…Currently, there is no theory for the posterior *consistency* in nonparametric *Bayesian*
quantile… …My family.
viii
ABSTRACT OF THE DISSERTATION
Nonparametric *Bayesian* Quantile Regression… …*Bayesian* approaches to quantile regression using
Dirichlet process mixture (DPM) models… …both the location
parameter and the scale parameter. The posterior *consistency* of our… …the idea of *Bayesian* quantile regression using Dirichlet
process mixture models where our…

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

APA (6^{th} Edition):

Chang, C. (2015). Nonparametric Bayesian Quantile Regression via Dirichlet Process Mixture Models. (Doctoral Dissertation). Washington University in St. Louis. Retrieved from https://openscholarship.wustl.edu/art_sci_etds/458

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

Chang, Chao. “Nonparametric Bayesian Quantile Regression via Dirichlet Process Mixture Models.” 2015. Doctoral Dissertation, Washington University in St. Louis. Accessed September 22, 2019. https://openscholarship.wustl.edu/art_sci_etds/458.

MLA Handbook (7^{th} Edition):

Chang, Chao. “Nonparametric Bayesian Quantile Regression via Dirichlet Process Mixture Models.” 2015. Web. 22 Sep 2019.

Vancouver:

Chang C. Nonparametric Bayesian Quantile Regression via Dirichlet Process Mixture Models. [Internet] [Doctoral dissertation]. Washington University in St. Louis; 2015. [cited 2019 Sep 22]. Available from: https://openscholarship.wustl.edu/art_sci_etds/458.

Council of Science Editors:

Chang C. Nonparametric Bayesian Quantile Regression via Dirichlet Process Mixture Models. [Doctoral Dissertation]. Washington University in St. Louis; 2015. Available from: https://openscholarship.wustl.edu/art_sci_etds/458

8.
Li, Qiong.
* Bayesian* Estimation of Graphical Gaussian Models with Edges and Vertices Symmetries.

Degree: PhD, Mathematics & Statistics, 2017, York University

URL: http://hdl.handle.net/10315/33452

► We consider the *Bayesian* analysis of undirected graphical Gaussian models with edges and vertices symmetries. The graphical Gaussian models with equality constraints on the precision…
(more)

Subjects/Keywords: Statistics; Asymptotic normality; Bayesian estimator; Colored G-Wishart distribution; Conditional independence; Conjugate prior; Consistency; Marginal model; Metropolis-Hastings; Large deviation; Symmetry constraint.

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

APA (6^{th} Edition):

Li, Q. (2017). Bayesian Estimation of Graphical Gaussian Models with Edges and Vertices Symmetries. (Doctoral Dissertation). York University. Retrieved from http://hdl.handle.net/10315/33452

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

Li, Qiong. “Bayesian Estimation of Graphical Gaussian Models with Edges and Vertices Symmetries.” 2017. Doctoral Dissertation, York University. Accessed September 22, 2019. http://hdl.handle.net/10315/33452.

MLA Handbook (7^{th} Edition):

Li, Qiong. “Bayesian Estimation of Graphical Gaussian Models with Edges and Vertices Symmetries.” 2017. Web. 22 Sep 2019.

Vancouver:

Li Q. Bayesian Estimation of Graphical Gaussian Models with Edges and Vertices Symmetries. [Internet] [Doctoral dissertation]. York University; 2017. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10315/33452.

Council of Science Editors:

Li Q. Bayesian Estimation of Graphical Gaussian Models with Edges and Vertices Symmetries. [Doctoral Dissertation]. York University; 2017. Available from: http://hdl.handle.net/10315/33452

University of Florida

9.
Sparks, Douglas Kyle.
Posterior *Consistency* of *Bayesian* Regression Models.

Degree: PhD, Statistics, 2012, University of Florida

URL: http://ufdc.ufl.edu/UFE0044654

► We develop conditions for posterior *consistency* under a variety of *Bayesian* regression models, many of which are both necessary and sufficient. We allow the number…
(more)

Subjects/Keywords: Bayesian networks; Density; Frequentism; Mathematical independent variables; Multilevel models; Random variables; Regression analysis; Sample size; Statistics; Sufficient conditions; bayes – bayesian – consistency – dimensional – empirical – g – hierarchical – high – necessary – posterior – prior – regression – sufficient – zellner

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

APA (6^{th} Edition):

Sparks, D. K. (2012). Posterior Consistency of Bayesian Regression Models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044654

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

Sparks, Douglas Kyle. “Posterior Consistency of Bayesian Regression Models.” 2012. Doctoral Dissertation, University of Florida. Accessed September 22, 2019. http://ufdc.ufl.edu/UFE0044654.

MLA Handbook (7^{th} Edition):

Sparks, Douglas Kyle. “Posterior Consistency of Bayesian Regression Models.” 2012. Web. 22 Sep 2019.

Vancouver:

Sparks DK. Posterior Consistency of Bayesian Regression Models. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Sep 22]. Available from: http://ufdc.ufl.edu/UFE0044654.

Council of Science Editors:

Sparks DK. Posterior Consistency of Bayesian Regression Models. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044654

University of Leicester

10.
Li, Guangjie.
Essays on economic and econometric applications of *Bayesian* estimation and model comparison.

Degree: PhD, 2009, University of Leicester

URL: http://hdl.handle.net/2381/4792

► This thesis consists of three chapters on economic and econometric applications of *Bayesian* parameter estimation and model comparison. The first two chapters study the incidental…
(more)

Subjects/Keywords: 330.015195; model comparison model selection consistency in estimation incidental parameter problem Bayesian model averaging (BMA) Markov chain Monte Carlo (MCMC) dynamic panel data model with fixed effect, finance and growth seemingly unrelated regression (SUR) mode

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

APA (6^{th} Edition):

Li, G. (2009). Essays on economic and econometric applications of Bayesian estimation and model comparison. (Doctoral Dissertation). University of Leicester. Retrieved from http://hdl.handle.net/2381/4792

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

Li, Guangjie. “Essays on economic and econometric applications of Bayesian estimation and model comparison.” 2009. Doctoral Dissertation, University of Leicester. Accessed September 22, 2019. http://hdl.handle.net/2381/4792.

MLA Handbook (7^{th} Edition):

Li, Guangjie. “Essays on economic and econometric applications of Bayesian estimation and model comparison.” 2009. Web. 22 Sep 2019.

Vancouver:

Li G. Essays on economic and econometric applications of Bayesian estimation and model comparison. [Internet] [Doctoral dissertation]. University of Leicester; 2009. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/2381/4792.

Council of Science Editors:

Li G. Essays on economic and econometric applications of Bayesian estimation and model comparison. [Doctoral Dissertation]. University of Leicester; 2009. Available from: http://hdl.handle.net/2381/4792

11.
Pati, Debdeep.
* Bayesian* Nonparametric Modeling and Theory for Complex Data
.

Degree: 2012, Duke University

URL: http://hdl.handle.net/10161/5564

► The dissertation focuses on solving some important theoretical and methodological problems associated with *Bayesian* modeling of infinite dimensional `objects', popularly called nonparametric Bayes. The…
(more)

Subjects/Keywords: Statistics; Bayesian nonparametrics; convergence rates; density regression; Gaussian process; posterior consistency; shape modeling

…which make the study of posterior *consistency*
more interesting in nonparametric *Bayesian*… …60
3 *Bayesian* nonparametric regression with varying residual density
64
3.1… …Priors for Residual Distribution . . . . . . . . . . . . . . . . .
71
3.3
*Consistency*… …94
3.8
4 Posterior *consistency* in conditional density estimation
96
4.1
Introduction… …in conditional density estimation . . . . . . 102
4.4
Posterior *consistency* in MGLRx…

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

APA (6^{th} Edition):

Pati, D. (2012). Bayesian Nonparametric Modeling and Theory for Complex Data . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/5564

Not specified: Masters Thesis or Doctoral Dissertation

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

Pati, Debdeep. “Bayesian Nonparametric Modeling and Theory for Complex Data .” 2012. Thesis, Duke University. Accessed September 22, 2019. http://hdl.handle.net/10161/5564.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Pati, Debdeep. “Bayesian Nonparametric Modeling and Theory for Complex Data .” 2012. Web. 22 Sep 2019.

Vancouver:

Pati D. Bayesian Nonparametric Modeling and Theory for Complex Data . [Internet] [Thesis]. Duke University; 2012. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10161/5564.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pati D. Bayesian Nonparametric Modeling and Theory for Complex Data . [Thesis]. Duke University; 2012. Available from: http://hdl.handle.net/10161/5564

Not specified: Masters Thesis or Doctoral Dissertation

University of Florida

12. Dasgupta, Shibasish. High Dimensional Inference and Variable Selection.

Degree: PhD, Statistics, 2013, University of Florida

URL: http://ufdc.ufl.edu/UFE0045721

► This dissertation consists of three research projects. The first project focuses on asymptotic expansions of posteriors for generalized linear models (GLM) with canonical link functions…
(more)

Subjects/Keywords: Estimators; Generalized linear model; Linear models; Linear regression; Maximum likelihood estimations; Oracles; Regression analysis; Sample size; Statistical models; Statistics; asymptotic – bayesian – consistency – dimensional – expansion – glm – high – inference – kullback – lasso – leibler – normality – oracle – posterior – property – selection – variable

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

APA (6^{th} Edition):

Dasgupta, S. (2013). High Dimensional Inference and Variable Selection. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045721

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

Dasgupta, Shibasish. “High Dimensional Inference and Variable Selection.” 2013. Doctoral Dissertation, University of Florida. Accessed September 22, 2019. http://ufdc.ufl.edu/UFE0045721.

MLA Handbook (7^{th} Edition):

Dasgupta, Shibasish. “High Dimensional Inference and Variable Selection.” 2013. Web. 22 Sep 2019.

Vancouver:

Dasgupta S. High Dimensional Inference and Variable Selection. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Sep 22]. Available from: http://ufdc.ufl.edu/UFE0045721.

Council of Science Editors:

Dasgupta S. High Dimensional Inference and Variable Selection. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045721