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You searched for subject:( Bayesian models). Showing records 1 – 30 of 653 total matches.

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University of Cambridge

1. Bratières, Sébastien. Non-parametric Bayesian models for structured output prediction.

Degree: PhD, 2018, University of Cambridge

 Structured output prediction is a machine learning tasks in which an input object is not just assigned a single class, as in classification, but multiple,… (more)

Subjects/Keywords: machine learning; Bayesian models; probability

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

APA (6th Edition):

Bratières, S. (2018). Non-parametric Bayesian models for structured output prediction. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/274973 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744725

Chicago Manual of Style (16th Edition):

Bratières, Sébastien. “Non-parametric Bayesian models for structured output prediction.” 2018. Doctoral Dissertation, University of Cambridge. Accessed September 19, 2019. https://www.repository.cam.ac.uk/handle/1810/274973 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744725.

MLA Handbook (7th Edition):

Bratières, Sébastien. “Non-parametric Bayesian models for structured output prediction.” 2018. Web. 19 Sep 2019.

Vancouver:

Bratières S. Non-parametric Bayesian models for structured output prediction. [Internet] [Doctoral dissertation]. University of Cambridge; 2018. [cited 2019 Sep 19]. Available from: https://www.repository.cam.ac.uk/handle/1810/274973 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744725.

Council of Science Editors:

Bratières S. Non-parametric Bayesian models for structured output prediction. [Doctoral Dissertation]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/274973 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744725


Queensland University of Technology

2. Rolfe, Margaret Irene. Bayesian models for longitudinal data.

Degree: 2010, Queensland University of Technology

 Longitudinal data, where data are repeatedly observed or measured on a temporal basis of time or age provides the foundation of the analysis of processes… (more)

Subjects/Keywords: Bayesian models; longitudinal data

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

APA (6th Edition):

Rolfe, M. I. (2010). Bayesian models for longitudinal data. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/34435/

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):

Rolfe, Margaret Irene. “Bayesian models for longitudinal data.” 2010. Thesis, Queensland University of Technology. Accessed September 19, 2019. https://eprints.qut.edu.au/34435/.

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

MLA Handbook (7th Edition):

Rolfe, Margaret Irene. “Bayesian models for longitudinal data.” 2010. Web. 19 Sep 2019.

Vancouver:

Rolfe MI. Bayesian models for longitudinal data. [Internet] [Thesis]. Queensland University of Technology; 2010. [cited 2019 Sep 19]. Available from: https://eprints.qut.edu.au/34435/.

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

Council of Science Editors:

Rolfe MI. Bayesian models for longitudinal data. [Thesis]. Queensland University of Technology; 2010. Available from: https://eprints.qut.edu.au/34435/

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


Queensland University of Technology

3. Donald, Margaret. Using Bayesian methods for the estimation of uncertainty in complex statistical models.

Degree: 2011, Queensland University of Technology

 The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal… (more)

Subjects/Keywords: Bayesian methods; complex statistical models

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

APA (6th Edition):

Donald, M. (2011). Using Bayesian methods for the estimation of uncertainty in complex statistical models. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/47132/

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):

Donald, Margaret. “Using Bayesian methods for the estimation of uncertainty in complex statistical models.” 2011. Thesis, Queensland University of Technology. Accessed September 19, 2019. https://eprints.qut.edu.au/47132/.

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

MLA Handbook (7th Edition):

Donald, Margaret. “Using Bayesian methods for the estimation of uncertainty in complex statistical models.” 2011. Web. 19 Sep 2019.

Vancouver:

Donald M. Using Bayesian methods for the estimation of uncertainty in complex statistical models. [Internet] [Thesis]. Queensland University of Technology; 2011. [cited 2019 Sep 19]. Available from: https://eprints.qut.edu.au/47132/.

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

Council of Science Editors:

Donald M. Using Bayesian methods for the estimation of uncertainty in complex statistical models. [Thesis]. Queensland University of Technology; 2011. Available from: https://eprints.qut.edu.au/47132/

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


University of St. Andrews

4. Whalen, Andrew. Computational, experimental, and statistical analyses of social learning in humans and animals .

Degree: 2016, University of St. Andrews

 Social learning is ubiquitous among animals and humans and is thought to be critical to the widespread success of humans and to the development and… (more)

Subjects/Keywords: Social learning; Bayesian models

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

APA (6th Edition):

Whalen, A. (2016). Computational, experimental, and statistical analyses of social learning in humans and animals . (Thesis). University of St. Andrews. Retrieved from http://hdl.handle.net/10023/8822

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):

Whalen, Andrew. “Computational, experimental, and statistical analyses of social learning in humans and animals .” 2016. Thesis, University of St. Andrews. Accessed September 19, 2019. http://hdl.handle.net/10023/8822.

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

MLA Handbook (7th Edition):

Whalen, Andrew. “Computational, experimental, and statistical analyses of social learning in humans and animals .” 2016. Web. 19 Sep 2019.

Vancouver:

Whalen A. Computational, experimental, and statistical analyses of social learning in humans and animals . [Internet] [Thesis]. University of St. Andrews; 2016. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10023/8822.

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

Council of Science Editors:

Whalen A. Computational, experimental, and statistical analyses of social learning in humans and animals . [Thesis]. University of St. Andrews; 2016. Available from: http://hdl.handle.net/10023/8822

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


University of Cambridge

5. Bratières, Sébastien. Non-parametric Bayesian models for structured output prediction .

Degree: 2018, University of Cambridge

 Structured output prediction is a machine learning tasks in which an input object is not just assigned a single class, as in classification, but multiple,… (more)

Subjects/Keywords: machine learning; Bayesian models; probability

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

APA (6th Edition):

Bratières, S. (2018). Non-parametric Bayesian models for structured output prediction . (Thesis). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/274973

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):

Bratières, Sébastien. “Non-parametric Bayesian models for structured output prediction .” 2018. Thesis, University of Cambridge. Accessed September 19, 2019. https://www.repository.cam.ac.uk/handle/1810/274973.

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

MLA Handbook (7th Edition):

Bratières, Sébastien. “Non-parametric Bayesian models for structured output prediction .” 2018. Web. 19 Sep 2019.

Vancouver:

Bratières S. Non-parametric Bayesian models for structured output prediction . [Internet] [Thesis]. University of Cambridge; 2018. [cited 2019 Sep 19]. Available from: https://www.repository.cam.ac.uk/handle/1810/274973.

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

Council of Science Editors:

Bratières S. Non-parametric Bayesian models for structured output prediction . [Thesis]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/274973

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


University of New South Wales

6. Pullen, James. A Bayesian approach to mixture models and transdimensional Markov chains.

Degree: Economics, 2011, University of New South Wales

 A general Bayesian sampling method is developed that uses parallel chains to select betweenmodels and to average the predictive density over such models. The method… (more)

Subjects/Keywords: MCMC; Bayesian; Mixture models

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

APA (6th Edition):

Pullen, J. (2011). A Bayesian approach to mixture models and transdimensional Markov chains. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/51520 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10207/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Pullen, James. “A Bayesian approach to mixture models and transdimensional Markov chains.” 2011. Doctoral Dissertation, University of New South Wales. Accessed September 19, 2019. http://handle.unsw.edu.au/1959.4/51520 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10207/SOURCE02?view=true.

MLA Handbook (7th Edition):

Pullen, James. “A Bayesian approach to mixture models and transdimensional Markov chains.” 2011. Web. 19 Sep 2019.

Vancouver:

Pullen J. A Bayesian approach to mixture models and transdimensional Markov chains. [Internet] [Doctoral dissertation]. University of New South Wales; 2011. [cited 2019 Sep 19]. Available from: http://handle.unsw.edu.au/1959.4/51520 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10207/SOURCE02?view=true.

Council of Science Editors:

Pullen J. A Bayesian approach to mixture models and transdimensional Markov chains. [Doctoral Dissertation]. University of New South Wales; 2011. Available from: http://handle.unsw.edu.au/1959.4/51520 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10207/SOURCE02?view=true


North Carolina State University

7. Krachey, Matthew James. Hierarchical Bayesian application to instantaneous rates tag-return models.

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

 Natural mortality has always been a challenging quantity to estimate in harvested populations. The most common approaches to estimation include a regression model based on… (more)

Subjects/Keywords: Bayesian; Tag-return models

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

APA (6th Edition):

Krachey, M. J. (2009). Hierarchical Bayesian application to instantaneous rates tag-return models. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4299

Chicago Manual of Style (16th Edition):

Krachey, Matthew James. “Hierarchical Bayesian application to instantaneous rates tag-return models.” 2009. Doctoral Dissertation, North Carolina State University. Accessed September 19, 2019. http://www.lib.ncsu.edu/resolver/1840.16/4299.

MLA Handbook (7th Edition):

Krachey, Matthew James. “Hierarchical Bayesian application to instantaneous rates tag-return models.” 2009. Web. 19 Sep 2019.

Vancouver:

Krachey MJ. Hierarchical Bayesian application to instantaneous rates tag-return models. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2019 Sep 19]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4299.

Council of Science Editors:

Krachey MJ. Hierarchical Bayesian application to instantaneous rates tag-return models. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4299


The Ohio State University

8. Kim, Yong Ku. Bayesian multiresolution dynamic models.

Degree: PhD, Statistics, 2007, The Ohio State University

 Dynamic process models such as state space models or diffusion process models are widely used for many natural dynamic phenomena. Statistical modelling has been essential… (more)

Subjects/Keywords: Statistics; Bayesian analysis; Hierarchical multiresolution models; Spatial dynamic models; Bayesian sensitivity

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

APA (6th Edition):

Kim, Y. K. (2007). Bayesian multiresolution dynamic models. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1180465799

Chicago Manual of Style (16th Edition):

Kim, Yong Ku. “Bayesian multiresolution dynamic models.” 2007. Doctoral Dissertation, The Ohio State University. Accessed September 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1180465799.

MLA Handbook (7th Edition):

Kim, Yong Ku. “Bayesian multiresolution dynamic models.” 2007. Web. 19 Sep 2019.

Vancouver:

Kim YK. Bayesian multiresolution dynamic models. [Internet] [Doctoral dissertation]. The Ohio State University; 2007. [cited 2019 Sep 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1180465799.

Council of Science Editors:

Kim YK. Bayesian multiresolution dynamic models. [Doctoral Dissertation]. The Ohio State University; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1180465799


Duke University

9. PETRALIA, FRANCESCA. Structured Bayesian learning through mixture models .

Degree: 2013, Duke University

  In this thesis, we develop some Bayesian mixture density estimation for univariate and multivariate data. We start proposing a repulsive process favoring mixture components… (more)

Subjects/Keywords: Statistics; Bayesian density estimation; Bayesian Nonparametric; Mixture Models

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APA (6th Edition):

PETRALIA, F. (2013). Structured Bayesian learning through mixture models . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/8065

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):

PETRALIA, FRANCESCA. “Structured Bayesian learning through mixture models .” 2013. Thesis, Duke University. Accessed September 19, 2019. http://hdl.handle.net/10161/8065.

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

MLA Handbook (7th Edition):

PETRALIA, FRANCESCA. “Structured Bayesian learning through mixture models .” 2013. Web. 19 Sep 2019.

Vancouver:

PETRALIA F. Structured Bayesian learning through mixture models . [Internet] [Thesis]. Duke University; 2013. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10161/8065.

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

Council of Science Editors:

PETRALIA F. Structured Bayesian learning through mixture models . [Thesis]. Duke University; 2013. Available from: http://hdl.handle.net/10161/8065

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


University of Edinburgh

10. Caldararu, Silvia. Understanding and predicting global leaf phenology using satellite observations of vegetation.

Degree: PhD, 2013, University of Edinburgh

 Leaf phenology refers to the timing of leaf life cycle events and is essential to our understanding of the earth system as it impacts the… (more)

Subjects/Keywords: 578.4; phenology; global vegetation models; Bayesian methods

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APA (6th Edition):

Caldararu, S. (2013). Understanding and predicting global leaf phenology using satellite observations of vegetation. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/7627

Chicago Manual of Style (16th Edition):

Caldararu, Silvia. “Understanding and predicting global leaf phenology using satellite observations of vegetation.” 2013. Doctoral Dissertation, University of Edinburgh. Accessed September 19, 2019. http://hdl.handle.net/1842/7627.

MLA Handbook (7th Edition):

Caldararu, Silvia. “Understanding and predicting global leaf phenology using satellite observations of vegetation.” 2013. Web. 19 Sep 2019.

Vancouver:

Caldararu S. Understanding and predicting global leaf phenology using satellite observations of vegetation. [Internet] [Doctoral dissertation]. University of Edinburgh; 2013. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1842/7627.

Council of Science Editors:

Caldararu S. Understanding and predicting global leaf phenology using satellite observations of vegetation. [Doctoral Dissertation]. University of Edinburgh; 2013. Available from: http://hdl.handle.net/1842/7627


University of Alberta

11. Khatibisepehr, Shima. Bayesian Solutions to Multi-model Inferential Sensing Problems.

Degree: PhD, Department of Chemical and Materials Engineering, 2013, University of Alberta

 In many industrial plants, development and implementation of advanced monitoring and control techniques require real-time measurement of process quality variables. However, on-line acquisition of such… (more)

Subjects/Keywords: Bayesian Soft Sensor; Multiple Models; Inferential Sensor

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

APA (6th Edition):

Khatibisepehr, S. (2013). Bayesian Solutions to Multi-model Inferential Sensing Problems. (Doctoral Dissertation). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/j6731485d

Chicago Manual of Style (16th Edition):

Khatibisepehr, Shima. “Bayesian Solutions to Multi-model Inferential Sensing Problems.” 2013. Doctoral Dissertation, University of Alberta. Accessed September 19, 2019. https://era.library.ualberta.ca/files/j6731485d.

MLA Handbook (7th Edition):

Khatibisepehr, Shima. “Bayesian Solutions to Multi-model Inferential Sensing Problems.” 2013. Web. 19 Sep 2019.

Vancouver:

Khatibisepehr S. Bayesian Solutions to Multi-model Inferential Sensing Problems. [Internet] [Doctoral dissertation]. University of Alberta; 2013. [cited 2019 Sep 19]. Available from: https://era.library.ualberta.ca/files/j6731485d.

Council of Science Editors:

Khatibisepehr S. Bayesian Solutions to Multi-model Inferential Sensing Problems. [Doctoral Dissertation]. University of Alberta; 2013. Available from: https://era.library.ualberta.ca/files/j6731485d


Nelson Mandela Metropolitan University

12. Sarpong, Abeam Danso. Tolerance intervals for variance component models using a Bayesian simulation procedure.

Degree: Faculty of Science, 2013, Nelson Mandela Metropolitan University

 The estimation of variance components serves as an integral part of the evaluation of variation, and is of interest and required in a variety of… (more)

Subjects/Keywords: Bayesian statistical decision theory; Multilevel models (Statistics)

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APA (6th Edition):

Sarpong, A. D. (2013). Tolerance intervals for variance component models using a Bayesian simulation procedure. (Thesis). Nelson Mandela Metropolitan University. Retrieved from http://hdl.handle.net/10948/d1021025

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):

Sarpong, Abeam Danso. “Tolerance intervals for variance component models using a Bayesian simulation procedure.” 2013. Thesis, Nelson Mandela Metropolitan University. Accessed September 19, 2019. http://hdl.handle.net/10948/d1021025.

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

MLA Handbook (7th Edition):

Sarpong, Abeam Danso. “Tolerance intervals for variance component models using a Bayesian simulation procedure.” 2013. Web. 19 Sep 2019.

Vancouver:

Sarpong AD. Tolerance intervals for variance component models using a Bayesian simulation procedure. [Internet] [Thesis]. Nelson Mandela Metropolitan University; 2013. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10948/d1021025.

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

Council of Science Editors:

Sarpong AD. Tolerance intervals for variance component models using a Bayesian simulation procedure. [Thesis]. Nelson Mandela Metropolitan University; 2013. Available from: http://hdl.handle.net/10948/d1021025

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


Hong Kong University of Science and Technology

13. Chan, Yun Kwan. Link prediction via ranking with a multiple membership nonparametric Bayesian model.

Degree: 2012, Hong Kong University of Science and Technology

 Link prediction in complex networks has found applications in a wide range of real-world domains involving relational data. The goal is to predict some hidden… (more)

Subjects/Keywords: Bayesian statistical decision theory; Uncertainty  – Mathematical models

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

APA (6th Edition):

Chan, Y. K. (2012). Link prediction via ranking with a multiple membership nonparametric Bayesian model. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1198293 ; http://repository.ust.hk/ir/bitstream/1783.1-7759/1/th_redirect.html

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):

Chan, Yun Kwan. “Link prediction via ranking with a multiple membership nonparametric Bayesian model.” 2012. Thesis, Hong Kong University of Science and Technology. Accessed September 19, 2019. https://doi.org/10.14711/thesis-b1198293 ; http://repository.ust.hk/ir/bitstream/1783.1-7759/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Chan, Yun Kwan. “Link prediction via ranking with a multiple membership nonparametric Bayesian model.” 2012. Web. 19 Sep 2019.

Vancouver:

Chan YK. Link prediction via ranking with a multiple membership nonparametric Bayesian model. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2012. [cited 2019 Sep 19]. Available from: https://doi.org/10.14711/thesis-b1198293 ; http://repository.ust.hk/ir/bitstream/1783.1-7759/1/th_redirect.html.

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

Council of Science Editors:

Chan YK. Link prediction via ranking with a multiple membership nonparametric Bayesian model. [Thesis]. Hong Kong University of Science and Technology; 2012. Available from: https://doi.org/10.14711/thesis-b1198293 ; http://repository.ust.hk/ir/bitstream/1783.1-7759/1/th_redirect.html

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


Montana State University

14. Mashamba, Able. Bayesian optimization and uncertainty analysis of complex environmental models, with applications in watershed management.

Degree: College of Engineering, 2010, Montana State University

 This dissertation presents results of research in the development, testing and application of an automated calibration and uncertainty analysis framework for distributed environmental models based… (more)

Subjects/Keywords: Bayesian statistical decision theory.; Hydrologic models.

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APA (6th Edition):

Mashamba, A. (2010). Bayesian optimization and uncertainty analysis of complex environmental models, with applications in watershed management. (Thesis). Montana State University. Retrieved from https://scholarworks.montana.edu/xmlui/handle/1/1798

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):

Mashamba, Able. “Bayesian optimization and uncertainty analysis of complex environmental models, with applications in watershed management.” 2010. Thesis, Montana State University. Accessed September 19, 2019. https://scholarworks.montana.edu/xmlui/handle/1/1798.

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

MLA Handbook (7th Edition):

Mashamba, Able. “Bayesian optimization and uncertainty analysis of complex environmental models, with applications in watershed management.” 2010. Web. 19 Sep 2019.

Vancouver:

Mashamba A. Bayesian optimization and uncertainty analysis of complex environmental models, with applications in watershed management. [Internet] [Thesis]. Montana State University; 2010. [cited 2019 Sep 19]. Available from: https://scholarworks.montana.edu/xmlui/handle/1/1798.

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

Council of Science Editors:

Mashamba A. Bayesian optimization and uncertainty analysis of complex environmental models, with applications in watershed management. [Thesis]. Montana State University; 2010. Available from: https://scholarworks.montana.edu/xmlui/handle/1/1798

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


Cornell University

15. Wan, Muting. Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics .

Degree: 2015, Cornell University

 In recent years, sparse classification problems have emerged in many fields of study. Finite mixture models have been developed to facilitate Bayesian inference where parameter… (more)

Subjects/Keywords: Bayesian inference; Linear mixed models; Bioinformatics

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APA (6th Edition):

Wan, M. (2015). Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/39389

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):

Wan, Muting. “Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics .” 2015. Thesis, Cornell University. Accessed September 19, 2019. http://hdl.handle.net/1813/39389.

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

MLA Handbook (7th Edition):

Wan, Muting. “Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics .” 2015. Web. 19 Sep 2019.

Vancouver:

Wan M. Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics . [Internet] [Thesis]. Cornell University; 2015. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1813/39389.

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

Council of Science Editors:

Wan M. Model-Based Classification With Applications To High-Dimensional Data In Bioinformatics . [Thesis]. Cornell University; 2015. Available from: http://hdl.handle.net/1813/39389

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


Cornell University

16. Kristensen, Jesper. Uncertainty Quantification With Surrogate Models In Alloy Modeling .

Degree: 2015, Cornell University

 The success of computational materials science in designing the materials of the future relies on the computation of materials properties using temporally expensive computer codes.… (more)

Subjects/Keywords: Uncertainty quantification; Surrogate models; Bayesian probability theory

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APA (6th Edition):

Kristensen, J. (2015). Uncertainty Quantification With Surrogate Models In Alloy Modeling . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/40658

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):

Kristensen, Jesper. “Uncertainty Quantification With Surrogate Models In Alloy Modeling .” 2015. Thesis, Cornell University. Accessed September 19, 2019. http://hdl.handle.net/1813/40658.

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

MLA Handbook (7th Edition):

Kristensen, Jesper. “Uncertainty Quantification With Surrogate Models In Alloy Modeling .” 2015. Web. 19 Sep 2019.

Vancouver:

Kristensen J. Uncertainty Quantification With Surrogate Models In Alloy Modeling . [Internet] [Thesis]. Cornell University; 2015. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/1813/40658.

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

Council of Science Editors:

Kristensen J. Uncertainty Quantification With Surrogate Models In Alloy Modeling . [Thesis]. Cornell University; 2015. Available from: http://hdl.handle.net/1813/40658

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


University of New South Wales

17. Gan, Quan. Topics in econometrics.

Degree: Economics, 2013, University of New South Wales

 Multivariate data modelling is an important and growing area of econometrics. There are two general approaches of modelling multivariate data: 1) modelling margins and copula… (more)

Subjects/Keywords: Skew-t Distribution; Bayesian methods; Factor models

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APA (6th Edition):

Gan, Q. (2013). Topics in econometrics. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/53308 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12003/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Gan, Quan. “Topics in econometrics.” 2013. Doctoral Dissertation, University of New South Wales. Accessed September 19, 2019. http://handle.unsw.edu.au/1959.4/53308 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12003/SOURCE02?view=true.

MLA Handbook (7th Edition):

Gan, Quan. “Topics in econometrics.” 2013. Web. 19 Sep 2019.

Vancouver:

Gan Q. Topics in econometrics. [Internet] [Doctoral dissertation]. University of New South Wales; 2013. [cited 2019 Sep 19]. Available from: http://handle.unsw.edu.au/1959.4/53308 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12003/SOURCE02?view=true.

Council of Science Editors:

Gan Q. Topics in econometrics. [Doctoral Dissertation]. University of New South Wales; 2013. Available from: http://handle.unsw.edu.au/1959.4/53308 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:12003/SOURCE02?view=true


University of Adelaide

18. Webb, Michael Roy. New methodologies for modelling individual differences in cognition.

Degree: 2010, University of Adelaide

 Many evaluations of cognitive models rely on data that have been averaged or aggregated across all experimental subjects, and so fail to consider the possibility… (more)

Subjects/Keywords: cognitive models; individual differences; Bayesian graphical modelling

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APA (6th Edition):

Webb, M. R. (2010). New methodologies for modelling individual differences in cognition. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/62779

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):

Webb, Michael Roy. “New methodologies for modelling individual differences in cognition.” 2010. Thesis, University of Adelaide. Accessed September 19, 2019. http://hdl.handle.net/2440/62779.

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

MLA Handbook (7th Edition):

Webb, Michael Roy. “New methodologies for modelling individual differences in cognition.” 2010. Web. 19 Sep 2019.

Vancouver:

Webb MR. New methodologies for modelling individual differences in cognition. [Internet] [Thesis]. University of Adelaide; 2010. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/2440/62779.

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

Council of Science Editors:

Webb MR. New methodologies for modelling individual differences in cognition. [Thesis]. University of Adelaide; 2010. Available from: http://hdl.handle.net/2440/62779

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


Rutgers University

19. Wiedenhoeft, John. Dynamically compressed Bayesian hidden Markov models using Haar wavelets.

Degree: PhD, Computer Science, 2018, Rutgers University

 Hidden Markov Models (HMM) are a powerful and ubiquitous tool for segmentation and labeling in bioinformatics and beyond. Classic techniques to infer suitable model parameters… (more)

Subjects/Keywords: Bayesian field theory; Hidden Markov models

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APA (6th Edition):

Wiedenhoeft, J. (2018). Dynamically compressed Bayesian hidden Markov models using Haar wavelets. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/59275/

Chicago Manual of Style (16th Edition):

Wiedenhoeft, John. “Dynamically compressed Bayesian hidden Markov models using Haar wavelets.” 2018. Doctoral Dissertation, Rutgers University. Accessed September 19, 2019. https://rucore.libraries.rutgers.edu/rutgers-lib/59275/.

MLA Handbook (7th Edition):

Wiedenhoeft, John. “Dynamically compressed Bayesian hidden Markov models using Haar wavelets.” 2018. Web. 19 Sep 2019.

Vancouver:

Wiedenhoeft J. Dynamically compressed Bayesian hidden Markov models using Haar wavelets. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2019 Sep 19]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/59275/.

Council of Science Editors:

Wiedenhoeft J. Dynamically compressed Bayesian hidden Markov models using Haar wavelets. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/59275/


Virginia Tech

20. Metzger, Thomas Anthony. Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection.

Degree: PhD, Statistics, 2019, Virginia Tech

 Standard linear modeling approaches make potentially simplistic assumptions regarding the structure of categorical effects that may obfuscate more complex relationships governing data. For example, recent… (more)

Subjects/Keywords: model selection; heteroscedasticity; linear models; Bayesian

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APA (6th Edition):

Metzger, T. A. (2019). Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/93226

Chicago Manual of Style (16th Edition):

Metzger, Thomas Anthony. “Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection.” 2019. Doctoral Dissertation, Virginia Tech. Accessed September 19, 2019. http://hdl.handle.net/10919/93226.

MLA Handbook (7th Edition):

Metzger, Thomas Anthony. “Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection.” 2019. Web. 19 Sep 2019.

Vancouver:

Metzger TA. Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10919/93226.

Council of Science Editors:

Metzger TA. Detection of Latent Heteroscedasticity and Group-Based Regression Effects in Linear Models via Bayesian Model Selection. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/93226


Colorado State University

21. Ketz, Alison C. Hierarchical Bayesian models for population ecology.

Degree: PhD, Ecology, 2017, Colorado State University

Models, by their definition, are abstractions of the systems they describe and require a delicate balance of inclusion of information with reduction. Hierarchical Bayesian models(more)

Subjects/Keywords: Elk; Models; Ungulates; Hierarchical; Bayesian; Population Ecology

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APA (6th Edition):

Ketz, A. C. (2017). Hierarchical Bayesian models for population ecology. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/183885

Chicago Manual of Style (16th Edition):

Ketz, Alison C. “Hierarchical Bayesian models for population ecology.” 2017. Doctoral Dissertation, Colorado State University. Accessed September 19, 2019. http://hdl.handle.net/10217/183885.

MLA Handbook (7th Edition):

Ketz, Alison C. “Hierarchical Bayesian models for population ecology.” 2017. Web. 19 Sep 2019.

Vancouver:

Ketz AC. Hierarchical Bayesian models for population ecology. [Internet] [Doctoral dissertation]. Colorado State University; 2017. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10217/183885.

Council of Science Editors:

Ketz AC. Hierarchical Bayesian models for population ecology. [Doctoral Dissertation]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/183885


University of Texas – Austin

22. Wang, Su, 1985-. Distributional model on a diet : one-shot word learning from text only.

Degree: MA, Linguistics, 2018, University of Texas – Austin

 We test whether distributional models can do one-shot learning of definitional properties from text only. Using Bayesian models, we find that first learning overarching structure… (more)

Subjects/Keywords: Lexical semantics; Bayesian models; One-shot learning

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APA (6th Edition):

Wang, Su, 1. (2018). Distributional model on a diet : one-shot word learning from text only. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63495

Chicago Manual of Style (16th Edition):

Wang, Su, 1985-. “Distributional model on a diet : one-shot word learning from text only.” 2018. Masters Thesis, University of Texas – Austin. Accessed September 19, 2019. http://hdl.handle.net/2152/63495.

MLA Handbook (7th Edition):

Wang, Su, 1985-. “Distributional model on a diet : one-shot word learning from text only.” 2018. Web. 19 Sep 2019.

Vancouver:

Wang, Su 1. Distributional model on a diet : one-shot word learning from text only. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/2152/63495.

Council of Science Editors:

Wang, Su 1. Distributional model on a diet : one-shot word learning from text only. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63495


Universitat de Valencia

23. Martínez Minaya, Joaquín. Recent statistical advances and applications of species distribution modeling .

Degree: 2019, Universitat de Valencia

 En el mundo en que vivimos, producimos aproximadamente 2.5 quintillones de bytes de datos por día. Esta enorme cantidad de datos proviene de las redes… (more)

Subjects/Keywords: bayesian inference; inla; species distribution models; geostatistics

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APA (6th Edition):

Martínez Minaya, J. (2019). Recent statistical advances and applications of species distribution modeling . (Doctoral Dissertation). Universitat de Valencia. Retrieved from http://hdl.handle.net/10550/71315

Chicago Manual of Style (16th Edition):

Martínez Minaya, Joaquín. “Recent statistical advances and applications of species distribution modeling .” 2019. Doctoral Dissertation, Universitat de Valencia. Accessed September 19, 2019. http://hdl.handle.net/10550/71315.

MLA Handbook (7th Edition):

Martínez Minaya, Joaquín. “Recent statistical advances and applications of species distribution modeling .” 2019. Web. 19 Sep 2019.

Vancouver:

Martínez Minaya J. Recent statistical advances and applications of species distribution modeling . [Internet] [Doctoral dissertation]. Universitat de Valencia; 2019. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10550/71315.

Council of Science Editors:

Martínez Minaya J. Recent statistical advances and applications of species distribution modeling . [Doctoral Dissertation]. Universitat de Valencia; 2019. Available from: http://hdl.handle.net/10550/71315


Texas A&M University

24. 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 September 19, 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. 19 Sep 2019.

Vancouver:

Talluri R. Bayesian Gaussian Graphical models using sparse selection priors and their mixtures. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Sep 19]. 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


Universitat de Valencia

25. Amorós Salvador, Rubén. Bayesian temporal and spatio-temporal Markov switching models for the detection of influenza outbreaks .

Degree: 2017, Universitat de Valencia

 Influenza is a disease which affects millions of people every year and causes hundreds of thousends of deads every year. This disease causes substantial direct… (more)

Subjects/Keywords: outbreaks detection; markov switching models; influenza; bayesian; spatio-temporal models

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APA (6th Edition):

Amorós Salvador, R. (2017). Bayesian temporal and spatio-temporal Markov switching models for the detection of influenza outbreaks . (Doctoral Dissertation). Universitat de Valencia. Retrieved from http://hdl.handle.net/10550/59265

Chicago Manual of Style (16th Edition):

Amorós Salvador, Rubén. “Bayesian temporal and spatio-temporal Markov switching models for the detection of influenza outbreaks .” 2017. Doctoral Dissertation, Universitat de Valencia. Accessed September 19, 2019. http://hdl.handle.net/10550/59265.

MLA Handbook (7th Edition):

Amorós Salvador, Rubén. “Bayesian temporal and spatio-temporal Markov switching models for the detection of influenza outbreaks .” 2017. Web. 19 Sep 2019.

Vancouver:

Amorós Salvador R. Bayesian temporal and spatio-temporal Markov switching models for the detection of influenza outbreaks . [Internet] [Doctoral dissertation]. Universitat de Valencia; 2017. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10550/59265.

Council of Science Editors:

Amorós Salvador R. Bayesian temporal and spatio-temporal Markov switching models for the detection of influenza outbreaks . [Doctoral Dissertation]. Universitat de Valencia; 2017. Available from: http://hdl.handle.net/10550/59265


Universitat de Valencia

26. Pennino, Maria Grazia. Implementing ecosystem approach to fishery management: advances and new tools .

Degree: 2013, Universitat de Valencia

 Desde la antigüedad, la pesca ha sido una fuente importante de alimentos para la humanidad, así como fuente de empleo y beneficios económicos para quienes… (more)

Subjects/Keywords: species distribution models; ecosystem approach to fishery management; bayesian spatial models

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APA (6th Edition):

Pennino, M. G. (2013). Implementing ecosystem approach to fishery management: advances and new tools . (Doctoral Dissertation). Universitat de Valencia. Retrieved from http://hdl.handle.net/10550/30118

Chicago Manual of Style (16th Edition):

Pennino, Maria Grazia. “Implementing ecosystem approach to fishery management: advances and new tools .” 2013. Doctoral Dissertation, Universitat de Valencia. Accessed September 19, 2019. http://hdl.handle.net/10550/30118.

MLA Handbook (7th Edition):

Pennino, Maria Grazia. “Implementing ecosystem approach to fishery management: advances and new tools .” 2013. Web. 19 Sep 2019.

Vancouver:

Pennino MG. Implementing ecosystem approach to fishery management: advances and new tools . [Internet] [Doctoral dissertation]. Universitat de Valencia; 2013. [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10550/30118.

Council of Science Editors:

Pennino MG. Implementing ecosystem approach to fishery management: advances and new tools . [Doctoral Dissertation]. Universitat de Valencia; 2013. Available from: http://hdl.handle.net/10550/30118


The Ohio State University

27. Kunkel, Deborah Elizabeth. Anchored Bayesian Gaussian Mixture Models.

Degree: PhD, Statistics, 2018, The Ohio State University

 Finite Bayesian mixture models are often used to describe data arising from a heterogeneous population. If information is available about the differences among the groups… (more)

Subjects/Keywords: Statistics; Gaussian mixture models, label-switching, Bayesian mixture models

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APA (6th Edition):

Kunkel, D. E. (2018). Anchored Bayesian Gaussian Mixture Models. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1524134234501475

Chicago Manual of Style (16th Edition):

Kunkel, Deborah Elizabeth. “Anchored Bayesian Gaussian Mixture Models.” 2018. Doctoral Dissertation, The Ohio State University. Accessed September 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524134234501475.

MLA Handbook (7th Edition):

Kunkel, Deborah Elizabeth. “Anchored Bayesian Gaussian Mixture Models.” 2018. Web. 19 Sep 2019.

Vancouver:

Kunkel DE. Anchored Bayesian Gaussian Mixture Models. [Internet] [Doctoral dissertation]. The Ohio State University; 2018. [cited 2019 Sep 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1524134234501475.

Council of Science Editors:

Kunkel DE. Anchored Bayesian Gaussian Mixture Models. [Doctoral Dissertation]. The Ohio State University; 2018. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1524134234501475


University of Houston

28. Liutec, Carmen M. A Multi-Product Individual-Level Model for New Product Sales: Forecasting and Insights.

Degree: Marketing and Entrepreneurship, Department of, University of Houston

 We develop a novel approach for modeling new product trial and early repeat purchase behavior, and we apply this approach in the context of consumer… (more)

Subjects/Keywords: New product models; Bayesian models

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APA (6th Edition):

Liutec, C. M. (n.d.). A Multi-Product Individual-Level Model for New Product Sales: Forecasting and Insights. (Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/2783

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Liutec, Carmen M. “A Multi-Product Individual-Level Model for New Product Sales: Forecasting and Insights.” Thesis, University of Houston. Accessed September 19, 2019. http://hdl.handle.net/10657/2783.

Note: this citation may be lacking information needed for this citation format:
No year of publication.
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Liutec, Carmen M. “A Multi-Product Individual-Level Model for New Product Sales: Forecasting and Insights.” Web. 19 Sep 2019.

Note: this citation may be lacking information needed for this citation format:
No year of publication.

Vancouver:

Liutec CM. A Multi-Product Individual-Level Model for New Product Sales: Forecasting and Insights. [Internet] [Thesis]. University of Houston; [cited 2019 Sep 19]. Available from: http://hdl.handle.net/10657/2783.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.

Council of Science Editors:

Liutec CM. A Multi-Product Individual-Level Model for New Product Sales: Forecasting and Insights. [Thesis]. University of Houston; Available from: http://hdl.handle.net/10657/2783

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
No year of publication.


University of Oxford

29. Harrison, Jonathan U. Developing and applying modelling and Bayesian inference tools for developmental biology.

Degree: PhD, 2018, University of Oxford

 Developmental biology allows us to answer crucial questions about how patterned, polarized cells can organize robustly and repeatably to form living tissues and organisms. Quantitative… (more)

Subjects/Keywords: Bayesian statistics; Developmental biology  – Mathematical models; Biology – Mathematical models

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APA (6th Edition):

Harrison, J. U. (2018). Developing and applying modelling and Bayesian inference tools for developmental biology. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:1528bb66-a03a-431f-8a8d-4a7bd25a9843 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.780644

Chicago Manual of Style (16th Edition):

Harrison, Jonathan U. “Developing and applying modelling and Bayesian inference tools for developmental biology.” 2018. Doctoral Dissertation, University of Oxford. Accessed September 19, 2019. http://ora.ox.ac.uk/objects/uuid:1528bb66-a03a-431f-8a8d-4a7bd25a9843 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.780644.

MLA Handbook (7th Edition):

Harrison, Jonathan U. “Developing and applying modelling and Bayesian inference tools for developmental biology.” 2018. Web. 19 Sep 2019.

Vancouver:

Harrison JU. Developing and applying modelling and Bayesian inference tools for developmental biology. [Internet] [Doctoral dissertation]. University of Oxford; 2018. [cited 2019 Sep 19]. Available from: http://ora.ox.ac.uk/objects/uuid:1528bb66-a03a-431f-8a8d-4a7bd25a9843 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.780644.

Council of Science Editors:

Harrison JU. Developing and applying modelling and Bayesian inference tools for developmental biology. [Doctoral Dissertation]. University of Oxford; 2018. Available from: http://ora.ox.ac.uk/objects/uuid:1528bb66-a03a-431f-8a8d-4a7bd25a9843 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.780644


The Ohio State University

30. Yang, Hui. Adjusting for Bounding and Time-in-Sample Eects in the National Crime Victimization Survey (NCVS) Property Crime Rate Estimation.

Degree: PhD, Statistics, 2016, The Ohio State University

 In this study, we deal with two problems: rotation group bias and lack of bounding information for producing crime rate estimates using the National Crime… (more)

Subjects/Keywords: Statistics; rotation group bias, zero-inflated count models, multinomial count models, Bayesian models

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APA (6th Edition):

Yang, H. (2016). Adjusting for Bounding and Time-in-Sample Eects in the National Crime Victimization Survey (NCVS) Property Crime Rate Estimation. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1452167047

Chicago Manual of Style (16th Edition):

Yang, Hui. “Adjusting for Bounding and Time-in-Sample Eects in the National Crime Victimization Survey (NCVS) Property Crime Rate Estimation.” 2016. Doctoral Dissertation, The Ohio State University. Accessed September 19, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1452167047.

MLA Handbook (7th Edition):

Yang, Hui. “Adjusting for Bounding and Time-in-Sample Eects in the National Crime Victimization Survey (NCVS) Property Crime Rate Estimation.” 2016. Web. 19 Sep 2019.

Vancouver:

Yang H. Adjusting for Bounding and Time-in-Sample Eects in the National Crime Victimization Survey (NCVS) Property Crime Rate Estimation. [Internet] [Doctoral dissertation]. The Ohio State University; 2016. [cited 2019 Sep 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1452167047.

Council of Science Editors:

Yang H. Adjusting for Bounding and Time-in-Sample Eects in the National Crime Victimization Survey (NCVS) Property Crime Rate Estimation. [Doctoral Dissertation]. The Ohio State University; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1452167047

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