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

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1. Dunn, Jeffrey. Bayesian Epistemology and Having Evidence.

Degree: PhD, Philosophy, 2010, U of Massachusetts : PhD

Bayesian Epistemology is a general framework for thinking about agents who have beliefs that come in degrees. Theories in this framework give accounts of rational… (more)

Subjects/Keywords: bayesian; dutch book; evidence; rationality; reliabilism; Philosophy

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APA (6th Edition):

Dunn, J. (2010). Bayesian Epistemology and Having Evidence. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/273

Chicago Manual of Style (16th Edition):

Dunn, Jeffrey. “Bayesian Epistemology and Having Evidence.” 2010. Doctoral Dissertation, U of Massachusetts : PhD. Accessed September 22, 2019. https://scholarworks.umass.edu/open_access_dissertations/273.

MLA Handbook (7th Edition):

Dunn, Jeffrey. “Bayesian Epistemology and Having Evidence.” 2010. Web. 22 Sep 2019.

Vancouver:

Dunn J. Bayesian Epistemology and Having Evidence. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2010. [cited 2019 Sep 22]. Available from: https://scholarworks.umass.edu/open_access_dissertations/273.

Council of Science Editors:

Dunn J. Bayesian Epistemology and Having Evidence. [Doctoral Dissertation]. U of Massachusetts : PhD; 2010. Available from: https://scholarworks.umass.edu/open_access_dissertations/273


Universiteit Utrecht

2. Meekes, M. Sensitivity to Evidence in Probabilistic Networks.

Degree: 2013, Universiteit Utrecht

 The probabilistic network framework is an approach to apply probability theory to reasoning with uncertainty in knowledge-based systems. Whereas researchers have studied the properties of… (more)

Subjects/Keywords: bayesian networks; probabilistic networks; sensitivity analysis; probabilistic network pruning; evidence sensitivity set; evidence sensitivity function

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APA (6th Edition):

Meekes, M. (2013). Sensitivity to Evidence in Probabilistic Networks. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/286942

Chicago Manual of Style (16th Edition):

Meekes, M. “Sensitivity to Evidence in Probabilistic Networks.” 2013. Masters Thesis, Universiteit Utrecht. Accessed September 22, 2019. http://dspace.library.uu.nl:8080/handle/1874/286942.

MLA Handbook (7th Edition):

Meekes, M. “Sensitivity to Evidence in Probabilistic Networks.” 2013. Web. 22 Sep 2019.

Vancouver:

Meekes M. Sensitivity to Evidence in Probabilistic Networks. [Internet] [Masters thesis]. Universiteit Utrecht; 2013. [cited 2019 Sep 22]. Available from: http://dspace.library.uu.nl:8080/handle/1874/286942.

Council of Science Editors:

Meekes M. Sensitivity to Evidence in Probabilistic Networks. [Masters Thesis]. Universiteit Utrecht; 2013. Available from: http://dspace.library.uu.nl:8080/handle/1874/286942


University of Hong Kong

3. Tse, Ka-sze, Hayson. Bayesian network analysis of evidence in criminal court cases.

Degree: PhD, 2015, University of Hong Kong

When justice goes wrong, grave consequences entail. They are damaging to the standing of the legal system and people’s lives. Humans are not good at… (more)

Subjects/Keywords: Evidence, Criminal - China - Hong Kong; Bayesian statistical decision theory - Data processing

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APA (6th Edition):

Tse, Ka-sze, H. (2015). Bayesian network analysis of evidence in criminal court cases. (Doctoral Dissertation). University of Hong Kong. Retrieved from Tse, K. H. [謝家樹]. (2015). Bayesian network analysis of evidence in criminal court cases. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5543999 ; http://hdl.handle.net/10722/212618

Chicago Manual of Style (16th Edition):

Tse, Ka-sze, Hayson. “Bayesian network analysis of evidence in criminal court cases.” 2015. Doctoral Dissertation, University of Hong Kong. Accessed September 22, 2019. Tse, K. H. [謝家樹]. (2015). Bayesian network analysis of evidence in criminal court cases. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5543999 ; http://hdl.handle.net/10722/212618.

MLA Handbook (7th Edition):

Tse, Ka-sze, Hayson. “Bayesian network analysis of evidence in criminal court cases.” 2015. Web. 22 Sep 2019.

Vancouver:

Tse, Ka-sze H. Bayesian network analysis of evidence in criminal court cases. [Internet] [Doctoral dissertation]. University of Hong Kong; 2015. [cited 2019 Sep 22]. Available from: Tse, K. H. [謝家樹]. (2015). Bayesian network analysis of evidence in criminal court cases. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5543999 ; http://hdl.handle.net/10722/212618.

Council of Science Editors:

Tse, Ka-sze H. Bayesian network analysis of evidence in criminal court cases. [Doctoral Dissertation]. University of Hong Kong; 2015. Available from: Tse, K. H. [謝家樹]. (2015). Bayesian network analysis of evidence in criminal court cases. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5543999 ; http://hdl.handle.net/10722/212618


University of California – Irvine

4. Canac, Nicolas. Model Selection and Parameter Estimation in Neutrino Cosmology and High Energy Astrophysics Around the Galactic Center.

Degree: Physics, 2016, University of California – Irvine

 Understanding the particle nature of dark matter and determining the properties of neutrinos remain two of the most important questions within the physics community. Both… (more)

Subjects/Keywords: Physics; Astrophysics; bayesian evidence; Dark matter; Fermi; neutrinos; primordial power spectrum

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APA (6th Edition):

Canac, N. (2016). Model Selection and Parameter Estimation in Neutrino Cosmology and High Energy Astrophysics Around the Galactic Center. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/8368n23p

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):

Canac, Nicolas. “Model Selection and Parameter Estimation in Neutrino Cosmology and High Energy Astrophysics Around the Galactic Center.” 2016. Thesis, University of California – Irvine. Accessed September 22, 2019. http://www.escholarship.org/uc/item/8368n23p.

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

MLA Handbook (7th Edition):

Canac, Nicolas. “Model Selection and Parameter Estimation in Neutrino Cosmology and High Energy Astrophysics Around the Galactic Center.” 2016. Web. 22 Sep 2019.

Vancouver:

Canac N. Model Selection and Parameter Estimation in Neutrino Cosmology and High Energy Astrophysics Around the Galactic Center. [Internet] [Thesis]. University of California – Irvine; 2016. [cited 2019 Sep 22]. Available from: http://www.escholarship.org/uc/item/8368n23p.

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

Council of Science Editors:

Canac N. Model Selection and Parameter Estimation in Neutrino Cosmology and High Energy Astrophysics Around the Galactic Center. [Thesis]. University of California – Irvine; 2016. Available from: http://www.escholarship.org/uc/item/8368n23p

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


Queen Mary, University of London

5. Pauran, Nargis. Bayesian networks for health care support.

Degree: PhD, 2016, Queen Mary, University of London

Bayesian Networks (BNs) have been considered as a potentially useful technique in the health service domain since they were invented. Many authors have presented BNs… (more)

Subjects/Keywords: Electronic Engineering and Computer Science; Bayesian Networks; clinical evidence data

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APA (6th Edition):

Pauran, N. (2016). Bayesian networks for health care support. (Doctoral Dissertation). Queen Mary, University of London. Retrieved from http://qmro.qmul.ac.uk/xmlui/handle/123456789/13045 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.775267

Chicago Manual of Style (16th Edition):

Pauran, Nargis. “Bayesian networks for health care support.” 2016. Doctoral Dissertation, Queen Mary, University of London. Accessed September 22, 2019. http://qmro.qmul.ac.uk/xmlui/handle/123456789/13045 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.775267.

MLA Handbook (7th Edition):

Pauran, Nargis. “Bayesian networks for health care support.” 2016. Web. 22 Sep 2019.

Vancouver:

Pauran N. Bayesian networks for health care support. [Internet] [Doctoral dissertation]. Queen Mary, University of London; 2016. [cited 2019 Sep 22]. Available from: http://qmro.qmul.ac.uk/xmlui/handle/123456789/13045 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.775267.

Council of Science Editors:

Pauran N. Bayesian networks for health care support. [Doctoral Dissertation]. Queen Mary, University of London; 2016. Available from: http://qmro.qmul.ac.uk/xmlui/handle/123456789/13045 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.775267


Universiteit Utrecht

6. Rooij, R.P. van. Gaining insight in the solution space of the MPE problem when changing evidence or parameter values.

Degree: 2015, Universiteit Utrecht

 For Bayesian networks, the MPE problem is the problem of finding a configuration of all unobserved variables such that this configuration has the highest posterior… (more)

Subjects/Keywords: Bayesian Network; Most Probable Explanation; MPE; evidence; parameter; solution space; sibling set

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APA (6th Edition):

Rooij, R. P. v. (2015). Gaining insight in the solution space of the MPE problem when changing evidence or parameter values. (Masters Thesis). Universiteit Utrecht. Retrieved from http://dspace.library.uu.nl:8080/handle/1874/324379

Chicago Manual of Style (16th Edition):

Rooij, R P van. “Gaining insight in the solution space of the MPE problem when changing evidence or parameter values.” 2015. Masters Thesis, Universiteit Utrecht. Accessed September 22, 2019. http://dspace.library.uu.nl:8080/handle/1874/324379.

MLA Handbook (7th Edition):

Rooij, R P van. “Gaining insight in the solution space of the MPE problem when changing evidence or parameter values.” 2015. Web. 22 Sep 2019.

Vancouver:

Rooij RPv. Gaining insight in the solution space of the MPE problem when changing evidence or parameter values. [Internet] [Masters thesis]. Universiteit Utrecht; 2015. [cited 2019 Sep 22]. Available from: http://dspace.library.uu.nl:8080/handle/1874/324379.

Council of Science Editors:

Rooij RPv. Gaining insight in the solution space of the MPE problem when changing evidence or parameter values. [Masters Thesis]. Universiteit Utrecht; 2015. Available from: http://dspace.library.uu.nl:8080/handle/1874/324379


University of Oxford

7. Forbes, Peter G. M. Quantifying the strength of evidence in forensic fingerprints.

Degree: PhD, 2014, University of Oxford

 Part I presents a model for fingerprint matching using Bayesian alignment on unlabelled point sets. An efficient Monte Carlo algorithm is developed to calculate the… (more)

Subjects/Keywords: 519.5; Statistics; bayesian alignment; forensic identification; likelihood ratio; marked point process; weight of evidence

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APA (6th Edition):

Forbes, P. G. M. (2014). Quantifying the strength of evidence in forensic fingerprints. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:0915280a-22cc-429d-90dc-77f934d61dde ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627866

Chicago Manual of Style (16th Edition):

Forbes, Peter G M. “Quantifying the strength of evidence in forensic fingerprints.” 2014. Doctoral Dissertation, University of Oxford. Accessed September 22, 2019. http://ora.ox.ac.uk/objects/uuid:0915280a-22cc-429d-90dc-77f934d61dde ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627866.

MLA Handbook (7th Edition):

Forbes, Peter G M. “Quantifying the strength of evidence in forensic fingerprints.” 2014. Web. 22 Sep 2019.

Vancouver:

Forbes PGM. Quantifying the strength of evidence in forensic fingerprints. [Internet] [Doctoral dissertation]. University of Oxford; 2014. [cited 2019 Sep 22]. Available from: http://ora.ox.ac.uk/objects/uuid:0915280a-22cc-429d-90dc-77f934d61dde ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627866.

Council of Science Editors:

Forbes PGM. Quantifying the strength of evidence in forensic fingerprints. [Doctoral Dissertation]. University of Oxford; 2014. Available from: http://ora.ox.ac.uk/objects/uuid:0915280a-22cc-429d-90dc-77f934d61dde ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627866


Queen Mary, University of London

8. Yet, Barbaros. Bayesian networks for evidence based clinical decision support.

Degree: PhD, 2013, Queen Mary, University of London

Evidence based medicine (EBM) is defined as the use of best available evidence for decision making, and it has been the predominant paradigm in clinical… (more)

Subjects/Keywords: 616; Computer Science; Evidence based medicine; Medical statistics; Bayesian networks; Clinical decision-making

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APA (6th Edition):

Yet, B. (2013). Bayesian networks for evidence based clinical decision support. (Doctoral Dissertation). Queen Mary, University of London. Retrieved from http://qmro.qmul.ac.uk/xmlui/handle/123456789/9096 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667238

Chicago Manual of Style (16th Edition):

Yet, Barbaros. “Bayesian networks for evidence based clinical decision support.” 2013. Doctoral Dissertation, Queen Mary, University of London. Accessed September 22, 2019. http://qmro.qmul.ac.uk/xmlui/handle/123456789/9096 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667238.

MLA Handbook (7th Edition):

Yet, Barbaros. “Bayesian networks for evidence based clinical decision support.” 2013. Web. 22 Sep 2019.

Vancouver:

Yet B. Bayesian networks for evidence based clinical decision support. [Internet] [Doctoral dissertation]. Queen Mary, University of London; 2013. [cited 2019 Sep 22]. Available from: http://qmro.qmul.ac.uk/xmlui/handle/123456789/9096 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667238.

Council of Science Editors:

Yet B. Bayesian networks for evidence based clinical decision support. [Doctoral Dissertation]. Queen Mary, University of London; 2013. Available from: http://qmro.qmul.ac.uk/xmlui/handle/123456789/9096 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.667238


University of Minnesota

9. Murray, Thomas. Hierarchical models for combining nonexchangeable sources of survival and functional data.

Degree: PhD, Biostatistics, 2014, University of Minnesota

 Conventional approaches to statistical inference preclude structures that facilitate incorporation of partially informative supplemental information acquired from similar circumstances. Borrowing strength from supplemental data promises… (more)

Subjects/Keywords: Bayesian Analysis; Commensurate Priors; Evidence Synthesis; Functional Data Analysis; Supplemental Data; Survival Analysis

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APA (6th Edition):

Murray, T. (2014). Hierarchical models for combining nonexchangeable sources of survival and functional data. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/182785

Chicago Manual of Style (16th Edition):

Murray, Thomas. “Hierarchical models for combining nonexchangeable sources of survival and functional data.” 2014. Doctoral Dissertation, University of Minnesota. Accessed September 22, 2019. http://hdl.handle.net/11299/182785.

MLA Handbook (7th Edition):

Murray, Thomas. “Hierarchical models for combining nonexchangeable sources of survival and functional data.” 2014. Web. 22 Sep 2019.

Vancouver:

Murray T. Hierarchical models for combining nonexchangeable sources of survival and functional data. [Internet] [Doctoral dissertation]. University of Minnesota; 2014. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/11299/182785.

Council of Science Editors:

Murray T. Hierarchical models for combining nonexchangeable sources of survival and functional data. [Doctoral Dissertation]. University of Minnesota; 2014. Available from: http://hdl.handle.net/11299/182785

10. Ben Mrad, Ali. Observations probabilistes dans les réseaux bayésiens : Probabilistic evidence in bayesian networks.

Degree: Docteur es, Informatique, 2015, Valenciennes; École nationale d'Ingénieurs de Sfax (Tunisie)

Dans un réseau bayésien, une observation sur une variable signifie en général que cette variable est instanciée. Ceci signifie que l’observateur peut affirmer avec certitude… (more)

Subjects/Keywords: Intelligence artificielle; Incertitude; Modèle graphique probabiliste; Réseau bayésien; Observation; Observation incertaine; Observation probabiliste; Observation de vraisemblance.; Artificial intelligence; Uncertainty; Probabilistic graphical models; Bayesian network; Evidence; Uncertain evidence; Probabilistic evidence; Likelihood finding; Soft evidence; Virtual evidence.

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APA (6th Edition):

Ben Mrad, A. (2015). Observations probabilistes dans les réseaux bayésiens : Probabilistic evidence in bayesian networks. (Doctoral Dissertation). Valenciennes; École nationale d'Ingénieurs de Sfax (Tunisie). Retrieved from http://www.theses.fr/2015VALE0018

Chicago Manual of Style (16th Edition):

Ben Mrad, Ali. “Observations probabilistes dans les réseaux bayésiens : Probabilistic evidence in bayesian networks.” 2015. Doctoral Dissertation, Valenciennes; École nationale d'Ingénieurs de Sfax (Tunisie). Accessed September 22, 2019. http://www.theses.fr/2015VALE0018.

MLA Handbook (7th Edition):

Ben Mrad, Ali. “Observations probabilistes dans les réseaux bayésiens : Probabilistic evidence in bayesian networks.” 2015. Web. 22 Sep 2019.

Vancouver:

Ben Mrad A. Observations probabilistes dans les réseaux bayésiens : Probabilistic evidence in bayesian networks. [Internet] [Doctoral dissertation]. Valenciennes; École nationale d'Ingénieurs de Sfax (Tunisie); 2015. [cited 2019 Sep 22]. Available from: http://www.theses.fr/2015VALE0018.

Council of Science Editors:

Ben Mrad A. Observations probabilistes dans les réseaux bayésiens : Probabilistic evidence in bayesian networks. [Doctoral Dissertation]. Valenciennes; École nationale d'Ingénieurs de Sfax (Tunisie); 2015. Available from: http://www.theses.fr/2015VALE0018


Virginia Tech

11. Jinn, Nicole Mee-Hyaang. Toward Error-Statistical Principles of Evidence in Statistical Inference.

Degree: MA, Philosophy, 2014, Virginia Tech

 The context for this research is statistical inference, the process of making predictions or inferences about a population from observation and analyses of a sample.… (more)

Subjects/Keywords: Statistical Inference; Evidential/Inferential Interpretations; Evidence; Sampling distributions; Likelihood Principle; Bayesian methods; Error Statistics; Frequentist methods; Philosophy of Statistics; Statistics Education

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APA (6th Edition):

Jinn, N. M. (2014). Toward Error-Statistical Principles of Evidence in Statistical Inference. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/48420

Chicago Manual of Style (16th Edition):

Jinn, Nicole Mee-Hyaang. “Toward Error-Statistical Principles of Evidence in Statistical Inference.” 2014. Masters Thesis, Virginia Tech. Accessed September 22, 2019. http://hdl.handle.net/10919/48420.

MLA Handbook (7th Edition):

Jinn, Nicole Mee-Hyaang. “Toward Error-Statistical Principles of Evidence in Statistical Inference.” 2014. Web. 22 Sep 2019.

Vancouver:

Jinn NM. Toward Error-Statistical Principles of Evidence in Statistical Inference. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10919/48420.

Council of Science Editors:

Jinn NM. Toward Error-Statistical Principles of Evidence in Statistical Inference. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/48420

12. LEAHY, JOY. The Impact of Performing a Network Meta-Analysis with Imperfect Evidence.

Degree: School of Computer Science & Statistics. Discipline of Statistics, 2019, Trinity College Dublin

 Network meta-analysis (NMA) is an important aspect of evidence synthesis in a clinical setting, as it allows us to compare treatments which may not have… (more)

Subjects/Keywords: single arm; individual patient data; matching adjusted indirect comparison; network meta-analysis; observational evidence; Bayesian statistics

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APA (6th Edition):

LEAHY, J. (2019). The Impact of Performing a Network Meta-Analysis with Imperfect Evidence. (Thesis). Trinity College Dublin. Retrieved from http://hdl.handle.net/2262/86070

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):

LEAHY, JOY. “The Impact of Performing a Network Meta-Analysis with Imperfect Evidence.” 2019. Thesis, Trinity College Dublin. Accessed September 22, 2019. http://hdl.handle.net/2262/86070.

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

MLA Handbook (7th Edition):

LEAHY, JOY. “The Impact of Performing a Network Meta-Analysis with Imperfect Evidence.” 2019. Web. 22 Sep 2019.

Vancouver:

LEAHY J. The Impact of Performing a Network Meta-Analysis with Imperfect Evidence. [Internet] [Thesis]. Trinity College Dublin; 2019. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/2262/86070.

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

Council of Science Editors:

LEAHY J. The Impact of Performing a Network Meta-Analysis with Imperfect Evidence. [Thesis]. Trinity College Dublin; 2019. Available from: http://hdl.handle.net/2262/86070

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


Wayne State University

13. Leigh, Hillary. The Road Taken: A Between And Within Subjects Study Of Intervention Selection Decisions By Performance Improvement Professionals.

Degree: PhD, Instructional Technology, 2014, Wayne State University

  Background: In performance improvement, intervention selection is a complex decision that ought to be based on the best available evidence. Despite this, there is… (more)

Subjects/Keywords: Bayesian analysis; decision-making; evidence-based practice; intervention selection; performance improvement; subjective probability; Instructional Media Design; Organizational Behavior and Theory

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APA (6th Edition):

Leigh, H. (2014). The Road Taken: A Between And Within Subjects Study Of Intervention Selection Decisions By Performance Improvement Professionals. (Doctoral Dissertation). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_dissertations/1075

Chicago Manual of Style (16th Edition):

Leigh, Hillary. “The Road Taken: A Between And Within Subjects Study Of Intervention Selection Decisions By Performance Improvement Professionals.” 2014. Doctoral Dissertation, Wayne State University. Accessed September 22, 2019. https://digitalcommons.wayne.edu/oa_dissertations/1075.

MLA Handbook (7th Edition):

Leigh, Hillary. “The Road Taken: A Between And Within Subjects Study Of Intervention Selection Decisions By Performance Improvement Professionals.” 2014. Web. 22 Sep 2019.

Vancouver:

Leigh H. The Road Taken: A Between And Within Subjects Study Of Intervention Selection Decisions By Performance Improvement Professionals. [Internet] [Doctoral dissertation]. Wayne State University; 2014. [cited 2019 Sep 22]. Available from: https://digitalcommons.wayne.edu/oa_dissertations/1075.

Council of Science Editors:

Leigh H. The Road Taken: A Between And Within Subjects Study Of Intervention Selection Decisions By Performance Improvement Professionals. [Doctoral Dissertation]. Wayne State University; 2014. Available from: https://digitalcommons.wayne.edu/oa_dissertations/1075


University of Cambridge

14. Corbella, Alice. Statistical inference in stochastic/deterministic epidemic models to jointly estimate transmission and severity .

Degree: 2019, University of Cambridge

 This thesis explores the joint estimation of transmission and severity of infectious diseases, focussing on the specific case of influenza. Transmission governs the speed and… (more)

Subjects/Keywords: Bayesian Methods; Evidence Synthesis; Monte Carlo methods; State-space models; Epidemic models; Infectious disease dynamics; Multiple data; Transmission; Severity; Influenza

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APA (6th Edition):

Corbella, A. (2019). Statistical inference in stochastic/deterministic epidemic models to jointly estimate transmission and severity . (Thesis). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/294438

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):

Corbella, Alice. “Statistical inference in stochastic/deterministic epidemic models to jointly estimate transmission and severity .” 2019. Thesis, University of Cambridge. Accessed September 22, 2019. https://www.repository.cam.ac.uk/handle/1810/294438.

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

MLA Handbook (7th Edition):

Corbella, Alice. “Statistical inference in stochastic/deterministic epidemic models to jointly estimate transmission and severity .” 2019. Web. 22 Sep 2019.

Vancouver:

Corbella A. Statistical inference in stochastic/deterministic epidemic models to jointly estimate transmission and severity . [Internet] [Thesis]. University of Cambridge; 2019. [cited 2019 Sep 22]. Available from: https://www.repository.cam.ac.uk/handle/1810/294438.

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

Council of Science Editors:

Corbella A. Statistical inference in stochastic/deterministic epidemic models to jointly estimate transmission and severity . [Thesis]. University of Cambridge; 2019. Available from: https://www.repository.cam.ac.uk/handle/1810/294438

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


University of Cambridge

15. Higson, Edward John. Bayesian methods and machine learning in astrophysics.

Degree: PhD, 2019, University of Cambridge

 This thesis is concerned with methods for Bayesian inference and their applications in astrophysics. We principally discuss two related themes: advances in nested sampling (Chapters… (more)

Subjects/Keywords: Machine Learning; Bayesian Inference; Nested sampling; Cosmology; Black Holes; Gravitational Waves; Neural Networks; Regression; Astrophysics; Sparsity; Parameter Estimation; Bayesian Evidence; Bayesian; Statistics; Bayesian Sparse Reconstruction; Computational Methods; Error Analysis; Dynamic Nested Sampling; nestcheck; perfectns; dyPolyChord; dynesty; Image Processing; Sparse Reconstruction; Planck; diagnostic tests; PolyChord; MultiNest; Hubble Space Telescope; Fitting; Nonparametric statistics

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

APA (6th Edition):

Higson, E. J. (2019). Bayesian methods and machine learning in astrophysics. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/289728 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767929

Chicago Manual of Style (16th Edition):

Higson, Edward John. “Bayesian methods and machine learning in astrophysics.” 2019. Doctoral Dissertation, University of Cambridge. Accessed September 22, 2019. https://www.repository.cam.ac.uk/handle/1810/289728 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767929.

MLA Handbook (7th Edition):

Higson, Edward John. “Bayesian methods and machine learning in astrophysics.” 2019. Web. 22 Sep 2019.

Vancouver:

Higson EJ. Bayesian methods and machine learning in astrophysics. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2019 Sep 22]. Available from: https://www.repository.cam.ac.uk/handle/1810/289728 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767929.

Council of Science Editors:

Higson EJ. Bayesian methods and machine learning in astrophysics. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://www.repository.cam.ac.uk/handle/1810/289728 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.767929


Portland State University

16. Yee, King G. Bayesian inquiry: an approach to the use of experts.

Degree: PhD, Systems Science, 1976, Portland State University

  Subjective information is a valuable resource; however, decisionmakers often ignore it because of difficulties in eliciting it from assessors. This thesis is on Bayesian(more)

Subjects/Keywords: Operations research; Expert Evidence; Bayesian statistical decision theory; Decision making

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APA (6th Edition):

Yee, K. G. (1976). Bayesian inquiry: an approach to the use of experts. (Doctoral Dissertation). Portland State University. Retrieved from http://pdxscholar.library.pdx.edu/open_access_etds/597

Chicago Manual of Style (16th Edition):

Yee, King G. “Bayesian inquiry: an approach to the use of experts.” 1976. Doctoral Dissertation, Portland State University. Accessed September 22, 2019. http://pdxscholar.library.pdx.edu/open_access_etds/597.

MLA Handbook (7th Edition):

Yee, King G. “Bayesian inquiry: an approach to the use of experts.” 1976. Web. 22 Sep 2019.

Vancouver:

Yee KG. Bayesian inquiry: an approach to the use of experts. [Internet] [Doctoral dissertation]. Portland State University; 1976. [cited 2019 Sep 22]. Available from: http://pdxscholar.library.pdx.edu/open_access_etds/597.

Council of Science Editors:

Yee KG. Bayesian inquiry: an approach to the use of experts. [Doctoral Dissertation]. Portland State University; 1976. Available from: http://pdxscholar.library.pdx.edu/open_access_etds/597

17. Ortega-García, Javier. Robust estimation, interpretation and assessment of likelihood ratios in forensic speaker recognition.

Degree: 2018, Elsevier BV

Subjects/Keywords: Forensic Speaker Recognition; Evidence; Interpretation; Robust; Bayesian likelihood ratio; Tippett plots; Informática; Telecomunicaciones

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APA (6th Edition):

Ortega-García, J. (2018). Robust estimation, interpretation and assessment of likelihood ratios in forensic speaker recognition. (Thesis). Elsevier BV. Retrieved from http://hdl.handle.net/10486/663651

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):

Ortega-García, Javier. “Robust estimation, interpretation and assessment of likelihood ratios in forensic speaker recognition.” 2018. Thesis, Elsevier BV. Accessed September 22, 2019. http://hdl.handle.net/10486/663651.

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

MLA Handbook (7th Edition):

Ortega-García, Javier. “Robust estimation, interpretation and assessment of likelihood ratios in forensic speaker recognition.” 2018. Web. 22 Sep 2019.

Vancouver:

Ortega-García J. Robust estimation, interpretation and assessment of likelihood ratios in forensic speaker recognition. [Internet] [Thesis]. Elsevier BV; 2018. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10486/663651.

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

Council of Science Editors:

Ortega-García J. Robust estimation, interpretation and assessment of likelihood ratios in forensic speaker recognition. [Thesis]. Elsevier BV; 2018. Available from: http://hdl.handle.net/10486/663651

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

18. ZHENG XIAOHUI. HIERARCHICAL MODELLING FOR INFECTIOUS DISEASES.

Degree: 2014, National University of Singapore

Subjects/Keywords: Bayesian; hierarchical model; infectious diseases; evidence synthesis; optimal design; temporal trend

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APA (6th Edition):

XIAOHUI, Z. (2014). HIERARCHICAL MODELLING FOR INFECTIOUS DISEASES. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/77770

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):

XIAOHUI, ZHENG. “HIERARCHICAL MODELLING FOR INFECTIOUS DISEASES.” 2014. Thesis, National University of Singapore. Accessed September 22, 2019. http://scholarbank.nus.edu.sg/handle/10635/77770.

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

MLA Handbook (7th Edition):

XIAOHUI, ZHENG. “HIERARCHICAL MODELLING FOR INFECTIOUS DISEASES.” 2014. Web. 22 Sep 2019.

Vancouver:

XIAOHUI Z. HIERARCHICAL MODELLING FOR INFECTIOUS DISEASES. [Internet] [Thesis]. National University of Singapore; 2014. [cited 2019 Sep 22]. Available from: http://scholarbank.nus.edu.sg/handle/10635/77770.

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

Council of Science Editors:

XIAOHUI Z. HIERARCHICAL MODELLING FOR INFECTIOUS DISEASES. [Thesis]. National University of Singapore; 2014. Available from: http://scholarbank.nus.edu.sg/handle/10635/77770

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


University of South Carolina

19. Langevin, Scott. Knowledge Representation, Communication, and Update In Probability-Based Multiagent Systems.

Degree: PhD, Computer Science and Engineering, 2010, University of South Carolina

  In this dissertation, we define a cooperative multiagent system where the agents use locally designed Bayesian networks to represent their knowledge. Agents communi- cate… (more)

Subjects/Keywords: Computer Sciences; Electrical and Computer Engineering; Engineering; Physical Sciences and Mathematics; Bayesian networks; Distributed problem solving; Multiagent Systems; Probabilistic Reasoning; Sensor Fusion; Soft Evidence

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APA (6th Edition):

Langevin, S. (2010). Knowledge Representation, Communication, and Update In Probability-Based Multiagent Systems. (Doctoral Dissertation). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/788

Chicago Manual of Style (16th Edition):

Langevin, Scott. “Knowledge Representation, Communication, and Update In Probability-Based Multiagent Systems.” 2010. Doctoral Dissertation, University of South Carolina. Accessed September 22, 2019. https://scholarcommons.sc.edu/etd/788.

MLA Handbook (7th Edition):

Langevin, Scott. “Knowledge Representation, Communication, and Update In Probability-Based Multiagent Systems.” 2010. Web. 22 Sep 2019.

Vancouver:

Langevin S. Knowledge Representation, Communication, and Update In Probability-Based Multiagent Systems. [Internet] [Doctoral dissertation]. University of South Carolina; 2010. [cited 2019 Sep 22]. Available from: https://scholarcommons.sc.edu/etd/788.

Council of Science Editors:

Langevin S. Knowledge Representation, Communication, and Update In Probability-Based Multiagent Systems. [Doctoral Dissertation]. University of South Carolina; 2010. Available from: https://scholarcommons.sc.edu/etd/788


University of Florida

20. Guo, Peng-Cheng. Orbital Characterization of Multi-Object Exoplanetary Systems with Radial Velocity Observation.

Degree: PhD, Astronomy, 2012, University of Florida

 Exoplanets are the planets around stars other than the sun. The detection and characterization of exoplanetary systems nowadays is one of the fields of the… (more)

Subjects/Keywords: Estimators; Extrasolar planets; Modeling; Orbitals; Parametric models; Planets; Principal components analysis; Space observatories; Standard deviation; Velocity; bayesian  – evidence  – exoplanet  – keplerian  – mcmc  – model  – nbody  – orbit  – rv

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

APA (6th Edition):

Guo, P. (2012). Orbital Characterization of Multi-Object Exoplanetary Systems with Radial Velocity Observation. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044871

Chicago Manual of Style (16th Edition):

Guo, Peng-Cheng. “Orbital Characterization of Multi-Object Exoplanetary Systems with Radial Velocity Observation.” 2012. Doctoral Dissertation, University of Florida. Accessed September 22, 2019. http://ufdc.ufl.edu/UFE0044871.

MLA Handbook (7th Edition):

Guo, Peng-Cheng. “Orbital Characterization of Multi-Object Exoplanetary Systems with Radial Velocity Observation.” 2012. Web. 22 Sep 2019.

Vancouver:

Guo P. Orbital Characterization of Multi-Object Exoplanetary Systems with Radial Velocity Observation. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Sep 22]. Available from: http://ufdc.ufl.edu/UFE0044871.

Council of Science Editors:

Guo P. Orbital Characterization of Multi-Object Exoplanetary Systems with Radial Velocity Observation. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044871

21. Timmer, S.T. Designing and Understanding Forensic Bayesian Networks using Argumentation.

Degree: 2017, University Utrecht

 The rise of forensic evidence in court has confronted the legal domain with a number of difficulties. It appears that a communication gap may exist… (more)

Subjects/Keywords: Legal reasoning; Bayesian networks; Legal argumentation; Reasoning with evidence; Reasoning under uncertainty

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APA (6th Edition):

Timmer, S. T. (2017). Designing and Understanding Forensic Bayesian Networks using Argumentation. (Doctoral Dissertation). University Utrecht. Retrieved from http://dspace.library.uu.nl/handle/1874/345719 ; URN:NBN:NL:UI:10-1874-345719 ; urn:isbn:978-90-393-6695-0 ; URN:NBN:NL:UI:10-1874-345719 ; http://dspace.library.uu.nl/handle/1874/345719

Chicago Manual of Style (16th Edition):

Timmer, S T. “Designing and Understanding Forensic Bayesian Networks using Argumentation.” 2017. Doctoral Dissertation, University Utrecht. Accessed September 22, 2019. http://dspace.library.uu.nl/handle/1874/345719 ; URN:NBN:NL:UI:10-1874-345719 ; urn:isbn:978-90-393-6695-0 ; URN:NBN:NL:UI:10-1874-345719 ; http://dspace.library.uu.nl/handle/1874/345719.

MLA Handbook (7th Edition):

Timmer, S T. “Designing and Understanding Forensic Bayesian Networks using Argumentation.” 2017. Web. 22 Sep 2019.

Vancouver:

Timmer ST. Designing and Understanding Forensic Bayesian Networks using Argumentation. [Internet] [Doctoral dissertation]. University Utrecht; 2017. [cited 2019 Sep 22]. Available from: http://dspace.library.uu.nl/handle/1874/345719 ; URN:NBN:NL:UI:10-1874-345719 ; urn:isbn:978-90-393-6695-0 ; URN:NBN:NL:UI:10-1874-345719 ; http://dspace.library.uu.nl/handle/1874/345719.

Council of Science Editors:

Timmer ST. Designing and Understanding Forensic Bayesian Networks using Argumentation. [Doctoral Dissertation]. University Utrecht; 2017. Available from: http://dspace.library.uu.nl/handle/1874/345719 ; URN:NBN:NL:UI:10-1874-345719 ; urn:isbn:978-90-393-6695-0 ; URN:NBN:NL:UI:10-1874-345719 ; http://dspace.library.uu.nl/handle/1874/345719


Leiden University

22. Cereda, G. Current challenges in statistical DNA evidence evaluation.

Degree: 2017, Leiden University

 This thesis covers different problems concerning the evaluation of DNA evidence. It is mainly divided into two parts: the first regards the DIP-STR genotyping techniques.… (more)

Subjects/Keywords: DNA evidence evaluation; Bayesian statistics; Y-STR haplotypes; Rare type match; DNA evidence evaluation; Bayesian statistics; Y-STR haplotypes; Rare type match

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APA (6th Edition):

Cereda, G. (2017). Current challenges in statistical DNA evidence evaluation. (Doctoral Dissertation). Leiden University. Retrieved from http://hdl.handle.net/1887/45172

Chicago Manual of Style (16th Edition):

Cereda, G. “Current challenges in statistical DNA evidence evaluation.” 2017. Doctoral Dissertation, Leiden University. Accessed September 22, 2019. http://hdl.handle.net/1887/45172.

MLA Handbook (7th Edition):

Cereda, G. “Current challenges in statistical DNA evidence evaluation.” 2017. Web. 22 Sep 2019.

Vancouver:

Cereda G. Current challenges in statistical DNA evidence evaluation. [Internet] [Doctoral dissertation]. Leiden University; 2017. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1887/45172.

Council of Science Editors:

Cereda G. Current challenges in statistical DNA evidence evaluation. [Doctoral Dissertation]. Leiden University; 2017. Available from: http://hdl.handle.net/1887/45172


University of Canterbury

23. Taylor, Michael. Comparing forensic hypotheses from PCR results in cases involving mixtures of body fluids.

Degree: Dept. of Mathematics, 1995, University of Canterbury

 Likelihood ratios provide a convenient and widely-used measure for assessing the relative support for forensic hypotheses given certain evidence. We extend earlier work to provide… (more)

Subjects/Keywords: Polymerase chain reaction; DNA profiling; likelihood ratio; multiple locus profiles; Bayesian; evidence; forensics; Field of Research::01 - Mathematical Sciences

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APA (6th Edition):

Taylor, M. (1995). Comparing forensic hypotheses from PCR results in cases involving mixtures of body fluids. (Thesis). University of Canterbury. Retrieved from http://hdl.handle.net/10092/11403

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):

Taylor, Michael. “Comparing forensic hypotheses from PCR results in cases involving mixtures of body fluids.” 1995. Thesis, University of Canterbury. Accessed September 22, 2019. http://hdl.handle.net/10092/11403.

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

MLA Handbook (7th Edition):

Taylor, Michael. “Comparing forensic hypotheses from PCR results in cases involving mixtures of body fluids.” 1995. Web. 22 Sep 2019.

Vancouver:

Taylor M. Comparing forensic hypotheses from PCR results in cases involving mixtures of body fluids. [Internet] [Thesis]. University of Canterbury; 1995. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/10092/11403.

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

Council of Science Editors:

Taylor M. Comparing forensic hypotheses from PCR results in cases involving mixtures of body fluids. [Thesis]. University of Canterbury; 1995. Available from: http://hdl.handle.net/10092/11403

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


Technical University of Lisbon

24. Fonseca, Pedro Miguel Teles da. Digit analysis using Benford's Law : a bayesian approach.

Degree: 2016, Technical University of Lisbon

Mestrado em Econometria Aplicada e Previsão

A lei de Benford, regularidade empírica segundo a qual muitos dos conjuntos de números gerados sem intervenção humana exibem… (more)

Subjects/Keywords: Análise da Frequência dos Dígitos; Calibração do Valor-P; Lei de Benford; Medidas Condicionais de Evidencia; Selecção Bayesiana de Modelos; Testes de Hipoteses; Bayesian Model Selection; Benford's Law; Conditional Measures of Evidence; Digit Analysis; Hypothesis Testing; P-Value Calibration

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APA (6th Edition):

Fonseca, P. M. T. d. (2016). Digit analysis using Benford's Law : a bayesian approach. (Thesis). Technical University of Lisbon. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:www.repository.utl.pt:10400.5/13105

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):

Fonseca, Pedro Miguel Teles da. “Digit analysis using Benford's Law : a bayesian approach.” 2016. Thesis, Technical University of Lisbon. Accessed September 22, 2019. http://www.rcaap.pt/detail.jsp?id=oai:www.repository.utl.pt:10400.5/13105.

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

MLA Handbook (7th Edition):

Fonseca, Pedro Miguel Teles da. “Digit analysis using Benford's Law : a bayesian approach.” 2016. Web. 22 Sep 2019.

Vancouver:

Fonseca PMTd. Digit analysis using Benford's Law : a bayesian approach. [Internet] [Thesis]. Technical University of Lisbon; 2016. [cited 2019 Sep 22]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:www.repository.utl.pt:10400.5/13105.

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

Council of Science Editors:

Fonseca PMTd. Digit analysis using Benford's Law : a bayesian approach. [Thesis]. Technical University of Lisbon; 2016. Available from: http://www.rcaap.pt/detail.jsp?id=oai:www.repository.utl.pt:10400.5/13105

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


University of Vienna

25. Pellert, Max. Collective dynamics of multi-agent networks.

Degree: 2017, University of Vienna

Der zentrale wissenschaftliche Beitrag dieser Masterarbeit ist die Entwicklung und empirische Evaluation von IBE*, einer Synthese aus 'Jeffrey Conditionalization' und des 'Schlusses auf die beste… (more)

Subjects/Keywords: 08.32 Erkenntnistheorie; 54.76 Computersimulation; agentenbasierte Modellierung / Netzwerke / belief updating / formale Epistemologie / Schluss auf die beste Erklärung / bayesianische Inferenz / unsichere Evidenz; agent-based modeling / networks / belief updating / formal epistemology / inference to the best explanation / bayesian inference / uncertain evidence

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APA (6th Edition):

Pellert, M. (2017). Collective dynamics of multi-agent networks. (Thesis). University of Vienna. Retrieved from http://othes.univie.ac.at/50046/

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):

Pellert, Max. “Collective dynamics of multi-agent networks.” 2017. Thesis, University of Vienna. Accessed September 22, 2019. http://othes.univie.ac.at/50046/.

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

MLA Handbook (7th Edition):

Pellert, Max. “Collective dynamics of multi-agent networks.” 2017. Web. 22 Sep 2019.

Vancouver:

Pellert M. Collective dynamics of multi-agent networks. [Internet] [Thesis]. University of Vienna; 2017. [cited 2019 Sep 22]. Available from: http://othes.univie.ac.at/50046/.

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

Council of Science Editors:

Pellert M. Collective dynamics of multi-agent networks. [Thesis]. University of Vienna; 2017. Available from: http://othes.univie.ac.at/50046/

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

26. Boudaren, Mohamed El Yazid. Modèles graphiques évidentiels : Evidential graphical models.

Degree: Docteur es, Systèmes intelligents et Ingénierie des logiciels, 2014, Evry, Institut national des télécommunications; Université des sciences et de la technologie Houari Boumediene (Alger)

Les modélisations par chaînes de Markov cachées permettent de résoudre un grand nombre de problèmes inverses se posant en traitement d’images ou de signaux. En… (more)

Subjects/Keywords: Chaînes de Markov cachées; Chaînes de Markov couples; Chaînes de Markov triplets; Segmentation non-supervisée; Estimation bayésienne; Estimation des paramètres; Données non-stationnaires; Théorie de l'évidence; Hidden Markov chains; Pairwise Markov chains; Triplet Markov chains; Unsupervised segmentation; Bayesian estimation; Parameters estimation; Nonstationary data; Theory of evidence

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APA (6th Edition):

Boudaren, M. E. Y. (2014). Modèles graphiques évidentiels : Evidential graphical models. (Doctoral Dissertation). Evry, Institut national des télécommunications; Université des sciences et de la technologie Houari Boumediene (Alger). Retrieved from http://www.theses.fr/2014TELE0001

Chicago Manual of Style (16th Edition):

Boudaren, Mohamed El Yazid. “Modèles graphiques évidentiels : Evidential graphical models.” 2014. Doctoral Dissertation, Evry, Institut national des télécommunications; Université des sciences et de la technologie Houari Boumediene (Alger). Accessed September 22, 2019. http://www.theses.fr/2014TELE0001.

MLA Handbook (7th Edition):

Boudaren, Mohamed El Yazid. “Modèles graphiques évidentiels : Evidential graphical models.” 2014. Web. 22 Sep 2019.

Vancouver:

Boudaren MEY. Modèles graphiques évidentiels : Evidential graphical models. [Internet] [Doctoral dissertation]. Evry, Institut national des télécommunications; Université des sciences et de la technologie Houari Boumediene (Alger); 2014. [cited 2019 Sep 22]. Available from: http://www.theses.fr/2014TELE0001.

Council of Science Editors:

Boudaren MEY. Modèles graphiques évidentiels : Evidential graphical models. [Doctoral Dissertation]. Evry, Institut national des télécommunications; Université des sciences et de la technologie Houari Boumediene (Alger); 2014. Available from: http://www.theses.fr/2014TELE0001


University of Cambridge

27. Higson, Edward John. Bayesian Methods and Machine Learning in Astrophysics .

Degree: University of Cambridge

 This thesis is concerned with methods for Bayesian inference and their applications in astrophysics. We principally discuss two related themes: advances in nested sampling (Chapters… (more)

Subjects/Keywords: Machine Learning; Bayesian Inference; Nested sampling; Cosmology; Black Holes; Gravitational Waves; Neural Networks; Regression; Astrophysics; Sparsity; Parameter Estimation; Bayesian Evidence; Bayesian; Statistics; Bayesian Sparse Reconstruction; Computational Methods; Error Analysis; Dynamic Nested Sampling; nestcheck; perfectns; dyPolyChord; dynesty; Image Processing; Sparse Reconstruction; Planck; diagnostic tests; error analysis; PolyChord; MultiNest; Hubble Space Telescope; Fitting; Nonparametric statistics

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APA (6th Edition):

Higson, E. J. (n.d.). Bayesian Methods and Machine Learning in Astrophysics . (Thesis). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/289728

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):

Higson, Edward John. “Bayesian Methods and Machine Learning in Astrophysics .” Thesis, University of Cambridge. Accessed September 22, 2019. https://www.repository.cam.ac.uk/handle/1810/289728.

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):

Higson, Edward John. “Bayesian Methods and Machine Learning in Astrophysics .” Web. 22 Sep 2019.

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

Vancouver:

Higson EJ. Bayesian Methods and Machine Learning in Astrophysics . [Internet] [Thesis]. University of Cambridge; [cited 2019 Sep 22]. Available from: https://www.repository.cam.ac.uk/handle/1810/289728.

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:

Higson EJ. Bayesian Methods and Machine Learning in Astrophysics . [Thesis]. University of Cambridge; Available from: https://www.repository.cam.ac.uk/handle/1810/289728

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 Cambridge

28. Hee, Sonke. Computational Bayesian techniques applied to cosmology.

Degree: PhD, 2018, University of Cambridge

 This thesis presents work around 3 themes: dark energy, gravitational waves and Bayesian inference. Both dark energy and gravitational wave physics are not yet well… (more)

Subjects/Keywords: Bayesian inference; Cosmology; Dark Energy; LCDM; Quintessence; Statistics; Gravitational waves; Tests of GR; Computational acceleration; Nested Sampling; General Relativity; Multinest; PolyChord; Product Space MCMC; Model selection; Posterior odds; Posterior Odds Ratio; Bayes factors; Parameter estimation; Equation of state; Phantom Dark Energy; Microwave background radiation; CMB; Supernovae; Baryonic Acoustic Oscillations; Data constraints; Kullback Leibler Divergence; KL divergence; LIGO; Constraining power; Lyman alpha forest; Bayesian; Bayes theorem; Probability; Efficiency; Concordance model; Parameter reconstruction; Marginal Likelihood; Kerr waveform; Free-form reconstruction; w(z); w=-1; Cosmological constant; Model comparison; Evidence; CosmoMC; CAMB; Hyper-likelihood; Model averaging; Planck

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

APA (6th Edition):

Hee, S. (2018). Computational Bayesian techniques applied to cosmology. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/273346 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744549

Chicago Manual of Style (16th Edition):

Hee, Sonke. “Computational Bayesian techniques applied to cosmology.” 2018. Doctoral Dissertation, University of Cambridge. Accessed September 22, 2019. https://www.repository.cam.ac.uk/handle/1810/273346 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744549.

MLA Handbook (7th Edition):

Hee, Sonke. “Computational Bayesian techniques applied to cosmology.” 2018. Web. 22 Sep 2019.

Vancouver:

Hee S. Computational Bayesian techniques applied to cosmology. [Internet] [Doctoral dissertation]. University of Cambridge; 2018. [cited 2019 Sep 22]. Available from: https://www.repository.cam.ac.uk/handle/1810/273346 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744549.

Council of Science Editors:

Hee S. Computational Bayesian techniques applied to cosmology. [Doctoral Dissertation]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/273346 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744549


University of Cambridge

29. Hee, Sonke. Computational Bayesian techniques applied to cosmology .

Degree: 2018, University of Cambridge

 This thesis presents work around 3 themes: dark energy, gravitational waves and Bayesian inference. Both dark energy and gravitational wave physics are not yet well… (more)

Subjects/Keywords: Bayesian inference; Cosmology; Dark Energy; LCDM; Quintessence; Statistics; Gravitational waves; Tests of GR; Computational acceleration; Nested Sampling; General Relativity; Multinest; PolyChord; Product Space MCMC; Model selection; Posterior odds; Posterior Odds Ratio; Bayes factors; Parameter estimation; Equation of state; Phantom Dark Energy; Microwave background radiation; CMB; Supernovae; Baryonic Acoustic Oscillations; Data constraints; Kullback Leibler Divergence; KL divergence; LIGO; Constraining power; Lyman alpha forest; Bayesian; Bayes theorem; Probability; Efficiency; Concordance model; Parameter reconstruction; Marginal Likelihood; Kerr waveform; Free-form reconstruction; w(z); w=-1; Cosmological constant; Model comparison; Evidence; CosmoMC; CAMB; Hyper-likelihood; Model averaging; Planck

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

APA (6th Edition):

Hee, S. (2018). Computational Bayesian techniques applied to cosmology . (Thesis). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/273346

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):

Hee, Sonke. “Computational Bayesian techniques applied to cosmology .” 2018. Thesis, University of Cambridge. Accessed September 22, 2019. https://www.repository.cam.ac.uk/handle/1810/273346.

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

MLA Handbook (7th Edition):

Hee, Sonke. “Computational Bayesian techniques applied to cosmology .” 2018. Web. 22 Sep 2019.

Vancouver:

Hee S. Computational Bayesian techniques applied to cosmology . [Internet] [Thesis]. University of Cambridge; 2018. [cited 2019 Sep 22]. Available from: https://www.repository.cam.ac.uk/handle/1810/273346.

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

Council of Science Editors:

Hee S. Computational Bayesian techniques applied to cosmology . [Thesis]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/273346

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

30. Claveau, Francois. Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects.

Degree: 2012, Erasmus School of Philosophy

 textabstractEconomists reason causally. Like many other scientists, they aim at formulating justified causal claims about their object of study. This thesis contributes to our understanding… (more)

Subjects/Keywords: Bayesian epistemology; design-based approach; deviant-case study; evidential variety; inferentialist semantics; philosophy of causality; philosophy of economics; referentialist semantics; structural approach; thesis; variety-of-evidence; vending-machine view

…can we gather compelling evidence for a causal claim?6 For scholars like me straddling… …of causal claims? Second, how can a causal claim be adequately supported by evidence… …alternative semantics. Similarly, I argue that one widespread way to gather strong evidence for a… …generalization appears to break down is already an achievement; it is evidence against the purported… …concept in the epistemology part—i.e., evidential variety—there is ample evidence of relevance… 

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

APA (6th Edition):

Claveau, F. (2012). Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects. (Doctoral Dissertation). Erasmus School of Philosophy. Retrieved from http://hdl.handle.net/1765/38242

Chicago Manual of Style (16th Edition):

Claveau, Francois. “Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects.” 2012. Doctoral Dissertation, Erasmus School of Philosophy. Accessed September 22, 2019. http://hdl.handle.net/1765/38242.

MLA Handbook (7th Edition):

Claveau, Francois. “Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects.” 2012. Web. 22 Sep 2019.

Vancouver:

Claveau F. Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects. [Internet] [Doctoral dissertation]. Erasmus School of Philosophy; 2012. [cited 2019 Sep 22]. Available from: http://hdl.handle.net/1765/38242.

Council of Science Editors:

Claveau F. Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects. [Doctoral Dissertation]. Erasmus School of Philosophy; 2012. Available from: http://hdl.handle.net/1765/38242

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