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You searched for subject:(bayesian consistency). Showing records 1 – 12 of 12 total matches.

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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

 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 (6th 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 (16th 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 (7th 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

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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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 Bayesian Models.

Degree: PhD, Statistics, 2016, University of Florida

 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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

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

 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 (6th 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 (16th 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 (7th 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

  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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

  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 (6th Edition):

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

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):

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

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

MLA Handbook (7th 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.

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

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

 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 (6th 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 (16th 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 (7th 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

.