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University of New South Wales

1. Peters, Gareth William. Advances in approximate Bayesian computation and trans-dimensional sampling methodology.

Degree: Mathematics & Statistics, 2010, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/50086 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9018/SOURCE02?view=true

► Bayesian statistical models continue to grow in complexity, drivenin part by a few key factors: the massive computational resourcesnow available to statisticians; the substantial gains…
(more)

Subjects/Keywords: Sequential Monte Carlo; Markov Chain Monte Carlo; Approximate Bayesian Computation

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

APA (6^{th} Edition):

Peters, G. W. (2010). Advances in approximate Bayesian computation and trans-dimensional sampling methodology. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/50086 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9018/SOURCE02?view=true

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

Peters, Gareth William. “Advances in approximate Bayesian computation and trans-dimensional sampling methodology.” 2010. Doctoral Dissertation, University of New South Wales. Accessed June 25, 2019. http://handle.unsw.edu.au/1959.4/50086 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9018/SOURCE02?view=true.

MLA Handbook (7^{th} Edition):

Peters, Gareth William. “Advances in approximate Bayesian computation and trans-dimensional sampling methodology.” 2010. Web. 25 Jun 2019.

Vancouver:

Peters GW. Advances in approximate Bayesian computation and trans-dimensional sampling methodology. [Internet] [Doctoral dissertation]. University of New South Wales; 2010. [cited 2019 Jun 25]. Available from: http://handle.unsw.edu.au/1959.4/50086 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9018/SOURCE02?view=true.

Council of Science Editors:

Peters GW. Advances in approximate Bayesian computation and trans-dimensional sampling methodology. [Doctoral Dissertation]. University of New South Wales; 2010. Available from: http://handle.unsw.edu.au/1959.4/50086 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:9018/SOURCE02?view=true

University of Southern California

2. Stram, Alexander H. Theoretical foundations of approximate Bayesian computation.

Degree: MA, Mathematics, 2015, University of Southern California

URL: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/558978/rec/7417

► We introduce *Monte* *Carlo* estimates with discussion of numerical integration and the curse of dimensionality, using a toy example of estimating π using a d−dimensional…
(more)

Subjects/Keywords: approximate Bayesian computation; Monte Carlo; sequential Monte Carlo; Bayesian statistics; importance sampling; sequential importance sampling

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APA (6^{th} Edition):

Stram, A. H. (2015). Theoretical foundations of approximate Bayesian computation. (Masters Thesis). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/558978/rec/7417

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

Stram, Alexander H. “Theoretical foundations of approximate Bayesian computation.” 2015. Masters Thesis, University of Southern California. Accessed June 25, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/558978/rec/7417.

MLA Handbook (7^{th} Edition):

Stram, Alexander H. “Theoretical foundations of approximate Bayesian computation.” 2015. Web. 25 Jun 2019.

Vancouver:

Stram AH. Theoretical foundations of approximate Bayesian computation. [Internet] [Masters thesis]. University of Southern California; 2015. [cited 2019 Jun 25]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/558978/rec/7417.

Council of Science Editors:

Stram AH. Theoretical foundations of approximate Bayesian computation. [Masters Thesis]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/558978/rec/7417

3. Buchholz, Alexander. High dimensional Bayesian computation : Computation bayésienne en grande dimension.

Degree: Docteur es, Mathématiques appliquées, 2018, Paris Saclay

URL: http://www.theses.fr/2018SACLG004

►

La statistique bayésienne computationnelle construit des approximations de la distribution a posteriori soit par échantillonnage, soit en construisant des approximations tractables. La contribution de cette… (more)

Subjects/Keywords: Monte Carlo sequentiel; Statistique bayesienne; Quasi Monte Carlo; Sequential Monte Carlo; Bayesian statistics; Quasi Monte Carlo; 519;

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

APA (6^{th} Edition):

Buchholz, A. (2018). High dimensional Bayesian computation : Computation bayésienne en grande dimension. (Doctoral Dissertation). Paris Saclay. Retrieved from http://www.theses.fr/2018SACLG004

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

Buchholz, Alexander. “High dimensional Bayesian computation : Computation bayésienne en grande dimension.” 2018. Doctoral Dissertation, Paris Saclay. Accessed June 25, 2019. http://www.theses.fr/2018SACLG004.

MLA Handbook (7^{th} Edition):

Buchholz, Alexander. “High dimensional Bayesian computation : Computation bayésienne en grande dimension.” 2018. Web. 25 Jun 2019.

Vancouver:

Buchholz A. High dimensional Bayesian computation : Computation bayésienne en grande dimension. [Internet] [Doctoral dissertation]. Paris Saclay; 2018. [cited 2019 Jun 25]. Available from: http://www.theses.fr/2018SACLG004.

Council of Science Editors:

Buchholz A. High dimensional Bayesian computation : Computation bayésienne en grande dimension. [Doctoral Dissertation]. Paris Saclay; 2018. Available from: http://www.theses.fr/2018SACLG004

4. Feliot, Paul. Une approche Bayésienne pour l'optimisation multi-objectif sous contraintes : A Bayesian approach to constrained multi-objective optimization.

Degree: Docteur es, Traitement du signal et des images, 2017, Paris Saclay

URL: http://www.theses.fr/2017SACLC045

►

Ces travaux de thèse portent sur l'optimisation multi-objectif de fonctions à valeurs réelles sous contraintes d'inégalités. En particulier, nous nous intéressons à des problèmes pour… (more)

Subjects/Keywords: Optimisation Bayésienne; Multi-objectif; Monte Carlo séquentiel; Bayesian optimization; Smulti-objective; Sequential Monte Carlo

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

APA (6^{th} Edition):

Feliot, P. (2017). Une approche Bayésienne pour l'optimisation multi-objectif sous contraintes : A Bayesian approach to constrained multi-objective optimization. (Doctoral Dissertation). Paris Saclay. Retrieved from http://www.theses.fr/2017SACLC045

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

Feliot, Paul. “Une approche Bayésienne pour l'optimisation multi-objectif sous contraintes : A Bayesian approach to constrained multi-objective optimization.” 2017. Doctoral Dissertation, Paris Saclay. Accessed June 25, 2019. http://www.theses.fr/2017SACLC045.

MLA Handbook (7^{th} Edition):

Feliot, Paul. “Une approche Bayésienne pour l'optimisation multi-objectif sous contraintes : A Bayesian approach to constrained multi-objective optimization.” 2017. Web. 25 Jun 2019.

Vancouver:

Feliot P. Une approche Bayésienne pour l'optimisation multi-objectif sous contraintes : A Bayesian approach to constrained multi-objective optimization. [Internet] [Doctoral dissertation]. Paris Saclay; 2017. [cited 2019 Jun 25]. Available from: http://www.theses.fr/2017SACLC045.

Council of Science Editors:

Feliot P. Une approche Bayésienne pour l'optimisation multi-objectif sous contraintes : A Bayesian approach to constrained multi-objective optimization. [Doctoral Dissertation]. Paris Saclay; 2017. Available from: http://www.theses.fr/2017SACLC045

5. Shatskikh, Katherine. Epidemic Detection in Two Populations.

Degree: 2017, University of California – eScholarship, University of California

URL: http://www.escholarship.org/uc/item/4x1556mb

► Traditional epidemic detection algorithms make decisions using only local information. We propose a novel approach that explicitly models spatial information fusion from several meta-populations. Our…
(more)

Subjects/Keywords: Statistics; Epidemiology; quickest detection; regression monte carlo; sequential regression monte carlo; stochastic epidemiological models

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APA (6^{th} Edition):

Shatskikh, K. (2017). Epidemic Detection in Two Populations. (Thesis). University of California – eScholarship, University of California. Retrieved from http://www.escholarship.org/uc/item/4x1556mb

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

Not specified: Masters Thesis or Doctoral Dissertation

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

Shatskikh, Katherine. “Epidemic Detection in Two Populations.” 2017. Thesis, University of California – eScholarship, University of California. Accessed June 25, 2019. http://www.escholarship.org/uc/item/4x1556mb.

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

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Shatskikh, Katherine. “Epidemic Detection in Two Populations.” 2017. Web. 25 Jun 2019.

Vancouver:

Shatskikh K. Epidemic Detection in Two Populations. [Internet] [Thesis]. University of California – eScholarship, University of California; 2017. [cited 2019 Jun 25]. Available from: http://www.escholarship.org/uc/item/4x1556mb.

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

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shatskikh K. Epidemic Detection in Two Populations. [Thesis]. University of California – eScholarship, University of California; 2017. Available from: http://www.escholarship.org/uc/item/4x1556mb

Not specified: Masters Thesis or Doctoral Dissertation

University of Melbourne

6.
Vu, Tuyet Thi Anh.
A Particle Markov Chain *Monte* *Carlo* algorithm for random finite set based multi-target tracking.

Degree: 2011, University of Melbourne

URL: http://hdl.handle.net/11343/36875

► The multi target tracking (MTT) problem is essentially that of estimating the presence and associated time trajectories of moving objects based on measurements from a…
(more)

Subjects/Keywords: multi-target tracking; Particle Markov Chain Monte Carlo; Markov Chain Monte Carlo; random sets; Sequential Monte Carlo

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APA (6^{th} Edition):

Vu, T. T. A. (2011). A Particle Markov Chain Monte Carlo algorithm for random finite set based multi-target tracking. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/36875

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

Vu, Tuyet Thi Anh. “A Particle Markov Chain Monte Carlo algorithm for random finite set based multi-target tracking.” 2011. Doctoral Dissertation, University of Melbourne. Accessed June 25, 2019. http://hdl.handle.net/11343/36875.

MLA Handbook (7^{th} Edition):

Vu, Tuyet Thi Anh. “A Particle Markov Chain Monte Carlo algorithm for random finite set based multi-target tracking.” 2011. Web. 25 Jun 2019.

Vancouver:

Vu TTA. A Particle Markov Chain Monte Carlo algorithm for random finite set based multi-target tracking. [Internet] [Doctoral dissertation]. University of Melbourne; 2011. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/11343/36875.

Council of Science Editors:

Vu TTA. A Particle Markov Chain Monte Carlo algorithm for random finite set based multi-target tracking. [Doctoral Dissertation]. University of Melbourne; 2011. Available from: http://hdl.handle.net/11343/36875

7. Minvielle-Larrousse, Pierre. Méthodes de simulation stochastique pour le traitement de l’information : Stochastic simulation methods for information processing.

Degree: Docteur es, Mathématiques, 2019, Pau

URL: http://www.theses.fr/2019PAUU3005

►

Lorsqu’une grandeur d’intérêt ne peut être directement mesurée, il est fréquent de procéder à l’observation d’autres quantités qui lui sont liées par des lois physiques.… (more)

Subjects/Keywords: Statistiques appliquées; Problème inverse; Monte Carlo séquentiel; Chaîne de Markov Monte Carlo; Applied statistics; Inverse problem; Sequential Monte Carlo; Markov Chain Monte Carlo; 510

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

APA (6^{th} Edition):

Minvielle-Larrousse, P. (2019). Méthodes de simulation stochastique pour le traitement de l’information : Stochastic simulation methods for information processing. (Doctoral Dissertation). Pau. Retrieved from http://www.theses.fr/2019PAUU3005

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

Minvielle-Larrousse, Pierre. “Méthodes de simulation stochastique pour le traitement de l’information : Stochastic simulation methods for information processing.” 2019. Doctoral Dissertation, Pau. Accessed June 25, 2019. http://www.theses.fr/2019PAUU3005.

MLA Handbook (7^{th} Edition):

Minvielle-Larrousse, Pierre. “Méthodes de simulation stochastique pour le traitement de l’information : Stochastic simulation methods for information processing.” 2019. Web. 25 Jun 2019.

Vancouver:

Minvielle-Larrousse P. Méthodes de simulation stochastique pour le traitement de l’information : Stochastic simulation methods for information processing. [Internet] [Doctoral dissertation]. Pau; 2019. [cited 2019 Jun 25]. Available from: http://www.theses.fr/2019PAUU3005.

Council of Science Editors:

Minvielle-Larrousse P. Méthodes de simulation stochastique pour le traitement de l’information : Stochastic simulation methods for information processing. [Doctoral Dissertation]. Pau; 2019. Available from: http://www.theses.fr/2019PAUU3005

Cleveland State University

8. Tumuluri, Uma. Nonlinear State Estimation in Polymer Electrolyte Membrane Fuel Cells.

Degree: MSin Chemical Engineering, Fenn College of Engineering, 2008, Cleveland State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=csu1231961499

► Research on alternative and renewable energy sources which are amicable to the environment has gained momentum because of the growing concern about the tremendous increase…
(more)

Subjects/Keywords: FUEL CELLS; sequential Monte Carlo; unscented Kalman filter

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APA (6^{th} Edition):

Tumuluri, U. (2008). Nonlinear State Estimation in Polymer Electrolyte Membrane Fuel Cells. (Masters Thesis). Cleveland State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=csu1231961499

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

Tumuluri, Uma. “Nonlinear State Estimation in Polymer Electrolyte Membrane Fuel Cells.” 2008. Masters Thesis, Cleveland State University. Accessed June 25, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=csu1231961499.

MLA Handbook (7^{th} Edition):

Tumuluri, Uma. “Nonlinear State Estimation in Polymer Electrolyte Membrane Fuel Cells.” 2008. Web. 25 Jun 2019.

Vancouver:

Tumuluri U. Nonlinear State Estimation in Polymer Electrolyte Membrane Fuel Cells. [Internet] [Masters thesis]. Cleveland State University; 2008. [cited 2019 Jun 25]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=csu1231961499.

Council of Science Editors:

Tumuluri U. Nonlinear State Estimation in Polymer Electrolyte Membrane Fuel Cells. [Masters Thesis]. Cleveland State University; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=csu1231961499

Virginia Tech

9. Hoegh, Andrew B. Predictive Model Fusion: A Modular Approach to Big, Unstructured Data.

Degree: PhD, Statistics, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/70921

► Data sets of increasing size and complexity require new approaches for prediction as the sheer volume of data from disparate sources inhibits joint processing and…
(more)

Subjects/Keywords: Model Fusion; Spatiotemporal Modeling; Areal Data; Sequential Monte Carlo

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

APA (6^{th} Edition):

Hoegh, A. B. (2016). Predictive Model Fusion: A Modular Approach to Big, Unstructured Data. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/70921

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

Hoegh, Andrew B. “Predictive Model Fusion: A Modular Approach to Big, Unstructured Data.” 2016. Doctoral Dissertation, Virginia Tech. Accessed June 25, 2019. http://hdl.handle.net/10919/70921.

MLA Handbook (7^{th} Edition):

Hoegh, Andrew B. “Predictive Model Fusion: A Modular Approach to Big, Unstructured Data.” 2016. Web. 25 Jun 2019.

Vancouver:

Hoegh AB. Predictive Model Fusion: A Modular Approach to Big, Unstructured Data. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10919/70921.

Council of Science Editors:

Hoegh AB. Predictive Model Fusion: A Modular Approach to Big, Unstructured Data. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/70921

University of Cambridge

10.
Yildirim, Sinan.
Maximum likelihood parameter estimation in time series models using *sequential* *Monte* * Carlo*.

Degree: PhD, 2013, University of Cambridge

URL: https://www.repository.cam.ac.uk/handle/1810/244707 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590211

► Time series models are used to characterise uncertainty in many real-world dynamical phenomena. A time series model typically contains a static variable, called parameter, which…
(more)

Subjects/Keywords: 519.5; Sequential Monte Carlo; Parameter estimation; Bayesian statistics

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

APA (6^{th} Edition):

Yildirim, S. (2013). Maximum likelihood parameter estimation in time series models using sequential Monte Carlo. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/244707 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590211

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

Yildirim, Sinan. “Maximum likelihood parameter estimation in time series models using sequential Monte Carlo.” 2013. Doctoral Dissertation, University of Cambridge. Accessed June 25, 2019. https://www.repository.cam.ac.uk/handle/1810/244707 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590211.

MLA Handbook (7^{th} Edition):

Yildirim, Sinan. “Maximum likelihood parameter estimation in time series models using sequential Monte Carlo.” 2013. Web. 25 Jun 2019.

Vancouver:

Yildirim S. Maximum likelihood parameter estimation in time series models using sequential Monte Carlo. [Internet] [Doctoral dissertation]. University of Cambridge; 2013. [cited 2019 Jun 25]. Available from: https://www.repository.cam.ac.uk/handle/1810/244707 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590211.

Council of Science Editors:

Yildirim S. Maximum likelihood parameter estimation in time series models using sequential Monte Carlo. [Doctoral Dissertation]. University of Cambridge; 2013. Available from: https://www.repository.cam.ac.uk/handle/1810/244707 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.590211

University of Illinois – Urbana-Champaign

11. Eisinger, Robert David. Sampling for conditional inference on contingency tables, multigraphs, and high dimensional tables.

Degree: PhD, Statistics, 2016, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/92928

► We propose new *sequential* importance sampling methods for sampling contingency tables with fixed margins, loopless, undirected multigraphs, and high-dimensional tables. In each case, the proposals…
(more)

Subjects/Keywords: Monte Carlo method; Sequential importance sampling; Counting problem; Contingency Table

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

APA (6^{th} Edition):

Eisinger, R. D. (2016). Sampling for conditional inference on contingency tables, multigraphs, and high dimensional tables. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/92928

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

Eisinger, Robert David. “Sampling for conditional inference on contingency tables, multigraphs, and high dimensional tables.” 2016. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed June 25, 2019. http://hdl.handle.net/2142/92928.

MLA Handbook (7^{th} Edition):

Eisinger, Robert David. “Sampling for conditional inference on contingency tables, multigraphs, and high dimensional tables.” 2016. Web. 25 Jun 2019.

Vancouver:

Eisinger RD. Sampling for conditional inference on contingency tables, multigraphs, and high dimensional tables. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2016. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/2142/92928.

Council of Science Editors:

Eisinger RD. Sampling for conditional inference on contingency tables, multigraphs, and high dimensional tables. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2016. Available from: http://hdl.handle.net/2142/92928

University of Arizona

12. Woodard, Aaron Jacob. Bayesian Estimation of a Single Mass Concentration Within an Asteroid .

Degree: 2017, University of Arizona

URL: http://hdl.handle.net/10150/625702

► Orbit determination has long relied on the use of the Kalman filter, or specifically the extended Kalman filter, as a means of accurately navigating spacecraft.…
(more)

Subjects/Keywords: Asteroid; Bayesian Estimation; Gravity Field; Sequential Monte Carlo Filter

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

APA (6^{th} Edition):

Woodard, A. J. (2017). Bayesian Estimation of a Single Mass Concentration Within an Asteroid . (Masters Thesis). University of Arizona. Retrieved from http://hdl.handle.net/10150/625702

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

Woodard, Aaron Jacob. “Bayesian Estimation of a Single Mass Concentration Within an Asteroid .” 2017. Masters Thesis, University of Arizona. Accessed June 25, 2019. http://hdl.handle.net/10150/625702.

MLA Handbook (7^{th} Edition):

Woodard, Aaron Jacob. “Bayesian Estimation of a Single Mass Concentration Within an Asteroid .” 2017. Web. 25 Jun 2019.

Vancouver:

Woodard AJ. Bayesian Estimation of a Single Mass Concentration Within an Asteroid . [Internet] [Masters thesis]. University of Arizona; 2017. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10150/625702.

Council of Science Editors:

Woodard AJ. Bayesian Estimation of a Single Mass Concentration Within an Asteroid . [Masters Thesis]. University of Arizona; 2017. Available from: http://hdl.handle.net/10150/625702

13. Chen, Yuting. Inférence bayésienne dans les modèles de croissance de plantes pour la prévision et la caractérisation des incertitudes : Bayesian inference in plant growth models for prediction and uncertainty assessment.

Degree: Docteur es, Mathématiques appliquées, 2014, Châtenay-Malabry, Ecole centrale de Paris

URL: http://www.theses.fr/2014ECAP0040

► La croissance des plantes en interaction avec l'environnement peut être décrite par des modèles mathématiques. Ceux-ci présentent des perspectives prometteuses pour un nombre considérable d'applications…
(more)

Subjects/Keywords: Chaînes de Markov; Méthode de Monte-Carlo séquentielle; Méthodes Bayésienne; Markov chains; Sequential Monte Carlo methods; Bayesian methods

Record Details Similar Records

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

APA (6^{th} Edition):

Chen, Y. (2014). Inférence bayésienne dans les modèles de croissance de plantes pour la prévision et la caractérisation des incertitudes : Bayesian inference in plant growth models for prediction and uncertainty assessment. (Doctoral Dissertation). Châtenay-Malabry, Ecole centrale de Paris. Retrieved from http://www.theses.fr/2014ECAP0040

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

Chen, Yuting. “Inférence bayésienne dans les modèles de croissance de plantes pour la prévision et la caractérisation des incertitudes : Bayesian inference in plant growth models for prediction and uncertainty assessment.” 2014. Doctoral Dissertation, Châtenay-Malabry, Ecole centrale de Paris. Accessed June 25, 2019. http://www.theses.fr/2014ECAP0040.

MLA Handbook (7^{th} Edition):

Chen, Yuting. “Inférence bayésienne dans les modèles de croissance de plantes pour la prévision et la caractérisation des incertitudes : Bayesian inference in plant growth models for prediction and uncertainty assessment.” 2014. Web. 25 Jun 2019.

Vancouver:

Chen Y. Inférence bayésienne dans les modèles de croissance de plantes pour la prévision et la caractérisation des incertitudes : Bayesian inference in plant growth models for prediction and uncertainty assessment. [Internet] [Doctoral dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2014. [cited 2019 Jun 25]. Available from: http://www.theses.fr/2014ECAP0040.

Council of Science Editors:

Chen Y. Inférence bayésienne dans les modèles de croissance de plantes pour la prévision et la caractérisation des incertitudes : Bayesian inference in plant growth models for prediction and uncertainty assessment. [Doctoral Dissertation]. Châtenay-Malabry, Ecole centrale de Paris; 2014. Available from: http://www.theses.fr/2014ECAP0040

University of Plymouth

14. Al-Saadony, Muhannad. Bayesian stochastic differential equation modelling with application to finance.

Degree: PhD, 2013, University of Plymouth

URL: http://hdl.handle.net/10026.1/1530

► In this thesis, we consider some popular stochastic differential equation models used in finance, such as the Vasicek Interest Rate model, the Heston model and…
(more)

Subjects/Keywords: 519.2; Fractional Stochastic Differential Equation, Bayesian inference, Markov chain Monte Carlo, Sequential Monte carlo Methods, Particle Filter, Auxiliary Particle Filter.

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

APA (6^{th} Edition):

Al-Saadony, M. (2013). Bayesian stochastic differential equation modelling with application to finance. (Doctoral Dissertation). University of Plymouth. Retrieved from http://hdl.handle.net/10026.1/1530

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

Al-Saadony, Muhannad. “Bayesian stochastic differential equation modelling with application to finance.” 2013. Doctoral Dissertation, University of Plymouth. Accessed June 25, 2019. http://hdl.handle.net/10026.1/1530.

MLA Handbook (7^{th} Edition):

Al-Saadony, Muhannad. “Bayesian stochastic differential equation modelling with application to finance.” 2013. Web. 25 Jun 2019.

Vancouver:

Al-Saadony M. Bayesian stochastic differential equation modelling with application to finance. [Internet] [Doctoral dissertation]. University of Plymouth; 2013. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10026.1/1530.

Council of Science Editors:

Al-Saadony M. Bayesian stochastic differential equation modelling with application to finance. [Doctoral Dissertation]. University of Plymouth; 2013. Available from: http://hdl.handle.net/10026.1/1530

15. Ridgway, James. Advances in computational Bayesian statistics and the approximation of Gibbs measures : Avancées en statistiques computationelles Bayesiennes et approximation de mesures de Gibbs.

Degree: Docteur es, Mathématiques appliquées, 2015, Paris 9

URL: http://www.theses.fr/2015PA090030

►

Ce mémoire de thèse regroupe plusieurs méthodes de calcul d'estimateur en statistiques bayésiennes. Plusieurs approches d'estimation seront considérées dans ce manuscrit. D'abord en estimation nous… (more)

Subjects/Keywords: Méthodes de Monte-Carlo séquentielles; Echantillonnage de Gibbs; Vb; Sequential Monte Carlo; Gibbs sampling; Variationnal Bayes; 519.5

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

APA (6^{th} Edition):

Ridgway, J. (2015). Advances in computational Bayesian statistics and the approximation of Gibbs measures : Avancées en statistiques computationelles Bayesiennes et approximation de mesures de Gibbs. (Doctoral Dissertation). Paris 9. Retrieved from http://www.theses.fr/2015PA090030

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

Ridgway, James. “Advances in computational Bayesian statistics and the approximation of Gibbs measures : Avancées en statistiques computationelles Bayesiennes et approximation de mesures de Gibbs.” 2015. Doctoral Dissertation, Paris 9. Accessed June 25, 2019. http://www.theses.fr/2015PA090030.

MLA Handbook (7^{th} Edition):

Ridgway, James. “Advances in computational Bayesian statistics and the approximation of Gibbs measures : Avancées en statistiques computationelles Bayesiennes et approximation de mesures de Gibbs.” 2015. Web. 25 Jun 2019.

Vancouver:

Ridgway J. Advances in computational Bayesian statistics and the approximation of Gibbs measures : Avancées en statistiques computationelles Bayesiennes et approximation de mesures de Gibbs. [Internet] [Doctoral dissertation]. Paris 9; 2015. [cited 2019 Jun 25]. Available from: http://www.theses.fr/2015PA090030.

Council of Science Editors:

Ridgway J. Advances in computational Bayesian statistics and the approximation of Gibbs measures : Avancées en statistiques computationelles Bayesiennes et approximation de mesures de Gibbs. [Doctoral Dissertation]. Paris 9; 2015. Available from: http://www.theses.fr/2015PA090030

University of Michigan

16. Park, Joon Ha. Computational Inference Algorithms for Spatiotemporal Processes and Other Complex Models.

Degree: PhD, Statistics, 2018, University of Michigan

URL: http://hdl.handle.net/2027.42/145801

► Data analysis can be carried out based on a stochastic model that reflects the analyst's understanding of how the system in question behaves. The stochastic…
(more)

Subjects/Keywords: computational inference; spatiotemporal process; partially observed Markov process; sequential Monte Carlo; Markov chain Monte Carlo; Statistics and Numeric Data; Science

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

APA (6^{th} Edition):

Park, J. H. (2018). Computational Inference Algorithms for Spatiotemporal Processes and Other Complex Models. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/145801

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

Park, Joon Ha. “Computational Inference Algorithms for Spatiotemporal Processes and Other Complex Models.” 2018. Doctoral Dissertation, University of Michigan. Accessed June 25, 2019. http://hdl.handle.net/2027.42/145801.

MLA Handbook (7^{th} Edition):

Park, Joon Ha. “Computational Inference Algorithms for Spatiotemporal Processes and Other Complex Models.” 2018. Web. 25 Jun 2019.

Vancouver:

Park JH. Computational Inference Algorithms for Spatiotemporal Processes and Other Complex Models. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/2027.42/145801.

Council of Science Editors:

Park JH. Computational Inference Algorithms for Spatiotemporal Processes and Other Complex Models. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/145801

University of Oxford

17.
Heng, Jeremy.
On the use of transport and optimal control methods for *Monte* *Carlo* simulation.

Degree: PhD, 2016, University of Oxford

URL: https://ora.ox.ac.uk/objects/uuid:6cbc7690-ac54-4a6a-b235-57fa62e5b2fc ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740797

► This thesis explores ideas from transport theory and optimal control to develop novel *Monte* *Carlo* methods to perform efficient statistical computation. The first project considers…
(more)

Subjects/Keywords: Transport theory – Statistical methods; Optimal control; Normalizing constants; Sequential Monte Carlo; Approximate dynamic programming; Monte Carlo; Mass transport; Annealed importance sampling; Reinforcement learning; Markov chain Monte Carlo

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

APA (6^{th} Edition):

Heng, J. (2016). On the use of transport and optimal control methods for Monte Carlo simulation. (Doctoral Dissertation). University of Oxford. Retrieved from https://ora.ox.ac.uk/objects/uuid:6cbc7690-ac54-4a6a-b235-57fa62e5b2fc ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740797

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

Heng, Jeremy. “On the use of transport and optimal control methods for Monte Carlo simulation.” 2016. Doctoral Dissertation, University of Oxford. Accessed June 25, 2019. https://ora.ox.ac.uk/objects/uuid:6cbc7690-ac54-4a6a-b235-57fa62e5b2fc ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740797.

MLA Handbook (7^{th} Edition):

Heng, Jeremy. “On the use of transport and optimal control methods for Monte Carlo simulation.” 2016. Web. 25 Jun 2019.

Vancouver:

Heng J. On the use of transport and optimal control methods for Monte Carlo simulation. [Internet] [Doctoral dissertation]. University of Oxford; 2016. [cited 2019 Jun 25]. Available from: https://ora.ox.ac.uk/objects/uuid:6cbc7690-ac54-4a6a-b235-57fa62e5b2fc ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740797.

Council of Science Editors:

Heng J. On the use of transport and optimal control methods for Monte Carlo simulation. [Doctoral Dissertation]. University of Oxford; 2016. Available from: https://ora.ox.ac.uk/objects/uuid:6cbc7690-ac54-4a6a-b235-57fa62e5b2fc ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.740797

The Ohio State University

18.
Schneider, Grant W.
Maximum Likelihood Estimation for Stochastic Differential
Equations Using *Sequential* Kriging-Based Optimization.

Degree: PhD, Statistics, 2014, The Ohio State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1406912247

► Stochastic differential equations (SDEs) are used as statistical models in many disciplines. However, intractable likelihood functions for SDEs make inference challenging, and we need to…
(more)

Subjects/Keywords: Statistics; Discretely sampled diffusions; Expected improvement; Gaussian process; Sequential Monte Carlo; Parameter estimation

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

APA (6^{th} Edition):

Schneider, G. W. (2014). Maximum Likelihood Estimation for Stochastic Differential Equations Using Sequential Kriging-Based Optimization. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1406912247

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

Schneider, Grant W. “Maximum Likelihood Estimation for Stochastic Differential Equations Using Sequential Kriging-Based Optimization.” 2014. Doctoral Dissertation, The Ohio State University. Accessed June 25, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406912247.

MLA Handbook (7^{th} Edition):

Schneider, Grant W. “Maximum Likelihood Estimation for Stochastic Differential Equations Using Sequential Kriging-Based Optimization.” 2014. Web. 25 Jun 2019.

Vancouver:

Schneider GW. Maximum Likelihood Estimation for Stochastic Differential Equations Using Sequential Kriging-Based Optimization. [Internet] [Doctoral dissertation]. The Ohio State University; 2014. [cited 2019 Jun 25]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1406912247.

Council of Science Editors:

Schneider GW. Maximum Likelihood Estimation for Stochastic Differential Equations Using Sequential Kriging-Based Optimization. [Doctoral Dissertation]. The Ohio State University; 2014. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1406912247

Georgia State University

19. Gu, Feng. Dynamic Data Driven Application System for Wildfire Spread Simulation.

Degree: PhD, Computer Science, 2010, Georgia State University

URL: https://scholarworks.gsu.edu/cs_diss/57

► Wildfires have significant impact on both ecosystems and human society. To effectively manage wildfires, simulation models are used to study and predict wildfire spread. The…
(more)

Subjects/Keywords: Wildfire spread; Modeling; Simulation; DEVS; DDDAS; Sequential Monte Carlo methods; Computer Sciences

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

APA (6^{th} Edition):

Gu, F. (2010). Dynamic Data Driven Application System for Wildfire Spread Simulation. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/cs_diss/57

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

Gu, Feng. “Dynamic Data Driven Application System for Wildfire Spread Simulation.” 2010. Doctoral Dissertation, Georgia State University. Accessed June 25, 2019. https://scholarworks.gsu.edu/cs_diss/57.

MLA Handbook (7^{th} Edition):

Gu, Feng. “Dynamic Data Driven Application System for Wildfire Spread Simulation.” 2010. Web. 25 Jun 2019.

Vancouver:

Gu F. Dynamic Data Driven Application System for Wildfire Spread Simulation. [Internet] [Doctoral dissertation]. Georgia State University; 2010. [cited 2019 Jun 25]. Available from: https://scholarworks.gsu.edu/cs_diss/57.

Council of Science Editors:

Gu F. Dynamic Data Driven Application System for Wildfire Spread Simulation. [Doctoral Dissertation]. Georgia State University; 2010. Available from: https://scholarworks.gsu.edu/cs_diss/57

Georgia State University

20.
Wu, Peisheng.
*SEQUENTIAL**MONTE* *CARLO* BASED DATA ASSIMILATION FRAMEWORK AND TOOLKIT FOR DYNAMIC SYSTEM SIMULATIONS.

Degree: PhD, Computer Science, 2017, Georgia State University

URL: https://scholarworks.gsu.edu/cs_diss/131

► Assimilating real-time sensor data into simulations is an effective approach for improving predictive abilities. However, integrating complex simulation models, e.g., discrete event simulation models…
(more)

Subjects/Keywords: Data Assimilation; Sequential Monte Carlo methods; particle filter; simulation; general framework; open source

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APA (6^{th} Edition):

Wu, P. (2017). SEQUENTIAL MONTE CARLO BASED DATA ASSIMILATION FRAMEWORK AND TOOLKIT FOR DYNAMIC SYSTEM SIMULATIONS. (Doctoral Dissertation). Georgia State University. Retrieved from https://scholarworks.gsu.edu/cs_diss/131

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

Wu, Peisheng. “SEQUENTIAL MONTE CARLO BASED DATA ASSIMILATION FRAMEWORK AND TOOLKIT FOR DYNAMIC SYSTEM SIMULATIONS.” 2017. Doctoral Dissertation, Georgia State University. Accessed June 25, 2019. https://scholarworks.gsu.edu/cs_diss/131.

MLA Handbook (7^{th} Edition):

Wu, Peisheng. “SEQUENTIAL MONTE CARLO BASED DATA ASSIMILATION FRAMEWORK AND TOOLKIT FOR DYNAMIC SYSTEM SIMULATIONS.” 2017. Web. 25 Jun 2019.

Vancouver:

Wu P. SEQUENTIAL MONTE CARLO BASED DATA ASSIMILATION FRAMEWORK AND TOOLKIT FOR DYNAMIC SYSTEM SIMULATIONS. [Internet] [Doctoral dissertation]. Georgia State University; 2017. [cited 2019 Jun 25]. Available from: https://scholarworks.gsu.edu/cs_diss/131.

Council of Science Editors:

Wu P. SEQUENTIAL MONTE CARLO BASED DATA ASSIMILATION FRAMEWORK AND TOOLKIT FOR DYNAMIC SYSTEM SIMULATIONS. [Doctoral Dissertation]. Georgia State University; 2017. Available from: https://scholarworks.gsu.edu/cs_diss/131

University of Tennessee – Knoxville

21.
To, Gary.
Quaternionic Attitude Estimation with Inertial Measuring Unit for Robotic and Human Body Motion Tracking using *Sequential* *Monte* *Carlo* Methods with Hyper-Dimensional Spherical Distributions.

Degree: 2012, University of Tennessee – Knoxville

URL: https://trace.tennessee.edu/utk_graddiss/1592

► This dissertation examined the inertial tracking technology for robotics and human tracking applications. This is a multi-discipline research that builds on the embedded system engineering,…
(more)

Subjects/Keywords: Motion Tracking; Sequential Monte Carlo; hyper-dimensional statistic; Biomedical Devices and Instrumentation

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

APA (6^{th} Edition):

To, G. (2012). Quaternionic Attitude Estimation with Inertial Measuring Unit for Robotic and Human Body Motion Tracking using Sequential Monte Carlo Methods with Hyper-Dimensional Spherical Distributions. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/1592

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

To, Gary. “Quaternionic Attitude Estimation with Inertial Measuring Unit for Robotic and Human Body Motion Tracking using Sequential Monte Carlo Methods with Hyper-Dimensional Spherical Distributions.” 2012. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed June 25, 2019. https://trace.tennessee.edu/utk_graddiss/1592.

MLA Handbook (7^{th} Edition):

To, Gary. “Quaternionic Attitude Estimation with Inertial Measuring Unit for Robotic and Human Body Motion Tracking using Sequential Monte Carlo Methods with Hyper-Dimensional Spherical Distributions.” 2012. Web. 25 Jun 2019.

Vancouver:

To G. Quaternionic Attitude Estimation with Inertial Measuring Unit for Robotic and Human Body Motion Tracking using Sequential Monte Carlo Methods with Hyper-Dimensional Spherical Distributions. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2012. [cited 2019 Jun 25]. Available from: https://trace.tennessee.edu/utk_graddiss/1592.

Council of Science Editors:

To G. Quaternionic Attitude Estimation with Inertial Measuring Unit for Robotic and Human Body Motion Tracking using Sequential Monte Carlo Methods with Hyper-Dimensional Spherical Distributions. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2012. Available from: https://trace.tennessee.edu/utk_graddiss/1592

University of Tennessee – Knoxville

22.
Kang, Kai.
Advanced *sequential* *Monte* *Carlo* methods and their applications to sparse sensor network for detection and estimation.

Degree: 2016, University of Tennessee – Knoxville

URL: https://trace.tennessee.edu/utk_graddiss/3933

► The general state space models present a flexible framework for modeling dynamic systems and therefore have vast applications in many disciplines such as engineering, economics,…
(more)

Subjects/Keywords: sequential Monte Carlo; multi-target tracking; wireless sensor network; homotopy; Applied Statistics; Probability; Statistical Theory

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

APA (6^{th} Edition):

Kang, K. (2016). Advanced sequential Monte Carlo methods and their applications to sparse sensor network for detection and estimation. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/3933

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

Kang, Kai. “Advanced sequential Monte Carlo methods and their applications to sparse sensor network for detection and estimation.” 2016. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed June 25, 2019. https://trace.tennessee.edu/utk_graddiss/3933.

MLA Handbook (7^{th} Edition):

Kang, Kai. “Advanced sequential Monte Carlo methods and their applications to sparse sensor network for detection and estimation.” 2016. Web. 25 Jun 2019.

Vancouver:

Kang K. Advanced sequential Monte Carlo methods and their applications to sparse sensor network for detection and estimation. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2016. [cited 2019 Jun 25]. Available from: https://trace.tennessee.edu/utk_graddiss/3933.

Council of Science Editors:

Kang K. Advanced sequential Monte Carlo methods and their applications to sparse sensor network for detection and estimation. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2016. Available from: https://trace.tennessee.edu/utk_graddiss/3933

University of California – Riverside

23. Gao, Chen. Metagenomic Binning Algorithms.

Degree: Applied Statistics, 2017, University of California – Riverside

URL: http://www.escholarship.org/uc/item/19j606dr

► Metagenomics is the study of DNAs of microorganisms that are taken directly from environmental samples without cultivation and isolation. Recently, the emerging field of metagenome…
(more)

Subjects/Keywords: Statistics; Bioinformatics; Binning algorithms; DirichletCluster; Dirichlet process; Metagenomics; Sequential Monte Carlo; Unsupervised

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APA (6^{th} Edition):

Gao, C. (2017). Metagenomic Binning Algorithms. (Thesis). University of California – Riverside. Retrieved from http://www.escholarship.org/uc/item/19j606dr

Not specified: Masters Thesis or Doctoral Dissertation

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

Gao, Chen. “Metagenomic Binning Algorithms.” 2017. Thesis, University of California – Riverside. Accessed June 25, 2019. http://www.escholarship.org/uc/item/19j606dr.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Gao, Chen. “Metagenomic Binning Algorithms.” 2017. Web. 25 Jun 2019.

Vancouver:

Gao C. Metagenomic Binning Algorithms. [Internet] [Thesis]. University of California – Riverside; 2017. [cited 2019 Jun 25]. Available from: http://www.escholarship.org/uc/item/19j606dr.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gao C. Metagenomic Binning Algorithms. [Thesis]. University of California – Riverside; 2017. Available from: http://www.escholarship.org/uc/item/19j606dr

Not specified: Masters Thesis or Doctoral Dissertation

University of Manchester

24. Syrri, Angeliki Lydia anton Ioannis. RELIABILITY AND RISK ANALYSIS OF POST FAULT CAPACITY SERVICES IN SMART DISTRIBUTION NETWORKS.

Degree: 2017, University of Manchester

URL: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307088

► Recent technological developments are bringing about substantial changes that are converting traditional distribution networks into “smart” distribution networks. In particular, it is possible to observe…
(more)

Subjects/Keywords: demand response, distribution network planning, differentiated reliability, distributed energy resources; sequential monte carlo simulation

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APA (6^{th} Edition):

Syrri, A. L. a. I. (2017). RELIABILITY AND RISK ANALYSIS OF POST FAULT CAPACITY SERVICES IN SMART DISTRIBUTION NETWORKS. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307088

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

Syrri, Angeliki Lydia anton Ioannis. “RELIABILITY AND RISK ANALYSIS OF POST FAULT CAPACITY SERVICES IN SMART DISTRIBUTION NETWORKS.” 2017. Doctoral Dissertation, University of Manchester. Accessed June 25, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307088.

MLA Handbook (7^{th} Edition):

Syrri, Angeliki Lydia anton Ioannis. “RELIABILITY AND RISK ANALYSIS OF POST FAULT CAPACITY SERVICES IN SMART DISTRIBUTION NETWORKS.” 2017. Web. 25 Jun 2019.

Vancouver:

Syrri ALaI. RELIABILITY AND RISK ANALYSIS OF POST FAULT CAPACITY SERVICES IN SMART DISTRIBUTION NETWORKS. [Internet] [Doctoral dissertation]. University of Manchester; 2017. [cited 2019 Jun 25]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307088.

Council of Science Editors:

Syrri ALaI. RELIABILITY AND RISK ANALYSIS OF POST FAULT CAPACITY SERVICES IN SMART DISTRIBUTION NETWORKS. [Doctoral Dissertation]. University of Manchester; 2017. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:307088

Duke University

25.
Marion, Joseph.
Finite Sample Bounds and Path Selection for *Sequential* *Monte* * Carlo*
.

Degree: 2018, Duke University

URL: http://hdl.handle.net/10161/17515

► *Sequential* *Monte* *Carlo* (SMC) samplers have received attention as an alternative to Markov chain *Monte* *Carlo* for Bayesian inference problems due to their strong…
(more)

Subjects/Keywords: Statistics; Bayesian Statistics; Computational Completity; Finite Sample Bounds; Path Sampling; Path Selection; Sequential Monte Carlo

Record Details Similar Records

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

APA (6^{th} Edition):

Marion, J. (2018). Finite Sample Bounds and Path Selection for Sequential Monte Carlo . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/17515

Not specified: Masters Thesis or Doctoral Dissertation

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

Marion, Joseph. “Finite Sample Bounds and Path Selection for Sequential Monte Carlo .” 2018. Thesis, Duke University. Accessed June 25, 2019. http://hdl.handle.net/10161/17515.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Marion, Joseph. “Finite Sample Bounds and Path Selection for Sequential Monte Carlo .” 2018. Web. 25 Jun 2019.

Vancouver:

Marion J. Finite Sample Bounds and Path Selection for Sequential Monte Carlo . [Internet] [Thesis]. Duke University; 2018. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10161/17515.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Marion J. Finite Sample Bounds and Path Selection for Sequential Monte Carlo . [Thesis]. Duke University; 2018. Available from: http://hdl.handle.net/10161/17515

Not specified: Masters Thesis or Doctoral Dissertation

The Ohio State University

26.
Lang, Lixin.
Advancing *Sequential* *Monte* *Carlo* For Model Checking, Prior
Smoothing And Applications In Engineering And Science.

Degree: PhD, Statistics, 2008, The Ohio State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1204582289

► The research effort in this dissertation is targeted to investigate theoretical properties of some key statistics used in the *sequential* *Monte* *Carlo* (SMC) sampling,…
(more)

Subjects/Keywords: Statistics; Sequential Monte Carlo; SMC; MCMC; Smoothing; Prior Checking; Predictive Density Value

Record Details Similar Records

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

APA (6^{th} Edition):

Lang, L. (2008). Advancing Sequential Monte Carlo For Model Checking, Prior Smoothing And Applications In Engineering And Science. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1204582289

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

Lang, Lixin. “Advancing Sequential Monte Carlo For Model Checking, Prior Smoothing And Applications In Engineering And Science.” 2008. Doctoral Dissertation, The Ohio State University. Accessed June 25, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1204582289.

MLA Handbook (7^{th} Edition):

Lang, Lixin. “Advancing Sequential Monte Carlo For Model Checking, Prior Smoothing And Applications In Engineering And Science.” 2008. Web. 25 Jun 2019.

Vancouver:

Lang L. Advancing Sequential Monte Carlo For Model Checking, Prior Smoothing And Applications In Engineering And Science. [Internet] [Doctoral dissertation]. The Ohio State University; 2008. [cited 2019 Jun 25]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1204582289.

Council of Science Editors:

Lang L. Advancing Sequential Monte Carlo For Model Checking, Prior Smoothing And Applications In Engineering And Science. [Doctoral Dissertation]. The Ohio State University; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1204582289

University of Adelaide

27. Haque, Qazi G M Ziaul. Bayesian estimation of monetary DSGE models and testing for indeterminacy.

Degree: 2018, University of Adelaide

URL: http://hdl.handle.net/2440/114258

► This thesis consists of three self-contained papers on U.S. monetary policy. The first paper examines monetary policy in the early 2000s, a prolonged period of…
(more)

Subjects/Keywords: Research by publication; monetary policy; Taylor rules; indeterminacy; trend inflation; Great Inflation; Sequential Monte Carlo

Record Details Similar Records

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

APA (6^{th} Edition):

Haque, Q. G. M. Z. (2018). Bayesian estimation of monetary DSGE models and testing for indeterminacy. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/114258

Not specified: Masters Thesis or Doctoral Dissertation

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

Haque, Qazi G M Ziaul. “Bayesian estimation of monetary DSGE models and testing for indeterminacy.” 2018. Thesis, University of Adelaide. Accessed June 25, 2019. http://hdl.handle.net/2440/114258.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Haque, Qazi G M Ziaul. “Bayesian estimation of monetary DSGE models and testing for indeterminacy.” 2018. Web. 25 Jun 2019.

Vancouver:

Haque QGMZ. Bayesian estimation of monetary DSGE models and testing for indeterminacy. [Internet] [Thesis]. University of Adelaide; 2018. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/2440/114258.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Haque QGMZ. Bayesian estimation of monetary DSGE models and testing for indeterminacy. [Thesis]. University of Adelaide; 2018. Available from: http://hdl.handle.net/2440/114258

Not specified: Masters Thesis or Doctoral Dissertation

University of Arkansas

28.
Ellis, Michael.
* Sequential* Inference for Hidden Markov Models.

Degree: MS, 2018, University of Arkansas

URL: https://scholarworks.uark.edu/etd/2963

► In many applications data are collected sequentially in time with very short time intervals between observations. If one is interested in using new observations…
(more)

Subjects/Keywords: Hidden Makrov Models; Sequential Monte Carlo Methods; State Space Models; Time Series Analysis; Applied Statistics

Record Details Similar Records

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

APA (6^{th} Edition):

Ellis, M. (2018). Sequential Inference for Hidden Markov Models. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/2963

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

Ellis, Michael. “Sequential Inference for Hidden Markov Models.” 2018. Masters Thesis, University of Arkansas. Accessed June 25, 2019. https://scholarworks.uark.edu/etd/2963.

MLA Handbook (7^{th} Edition):

Ellis, Michael. “Sequential Inference for Hidden Markov Models.” 2018. Web. 25 Jun 2019.

Vancouver:

Ellis M. Sequential Inference for Hidden Markov Models. [Internet] [Masters thesis]. University of Arkansas; 2018. [cited 2019 Jun 25]. Available from: https://scholarworks.uark.edu/etd/2963.

Council of Science Editors:

Ellis M. Sequential Inference for Hidden Markov Models. [Masters Thesis]. University of Arkansas; 2018. Available from: https://scholarworks.uark.edu/etd/2963

University of Toronto

29. Shabany, Mahdi. VLSI Implementation of Digital Signal Processing Algorithms for MIMO/SISO Systems.

Degree: 2009, University of Toronto

URL: http://hdl.handle.net/1807/17485

►

The efficient high-throughput VLSI implementation of near-optimal multiple-input multiple-output (MIMO) detectors for 4x4 MIMO systems in high-order quadrature amplitude modulation (QAM) schemes has been a… (more)

Subjects/Keywords: ASIC Implementation; K-Best MIMO Detector; Sequential Monte Carlo; Lattice Reduction; 0544

Record Details Similar Records

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

APA (6^{th} Edition):

Shabany, M. (2009). VLSI Implementation of Digital Signal Processing Algorithms for MIMO/SISO Systems. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/17485

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

Shabany, Mahdi. “VLSI Implementation of Digital Signal Processing Algorithms for MIMO/SISO Systems.” 2009. Doctoral Dissertation, University of Toronto. Accessed June 25, 2019. http://hdl.handle.net/1807/17485.

MLA Handbook (7^{th} Edition):

Shabany, Mahdi. “VLSI Implementation of Digital Signal Processing Algorithms for MIMO/SISO Systems.” 2009. Web. 25 Jun 2019.

Vancouver:

Shabany M. VLSI Implementation of Digital Signal Processing Algorithms for MIMO/SISO Systems. [Internet] [Doctoral dissertation]. University of Toronto; 2009. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/1807/17485.

Council of Science Editors:

Shabany M. VLSI Implementation of Digital Signal Processing Algorithms for MIMO/SISO Systems. [Doctoral Dissertation]. University of Toronto; 2009. Available from: http://hdl.handle.net/1807/17485

University of Manchester

30. Syrri, Angeliki Lydia Antonia. Reliability and risk analysis of post fault capacity services in smart distribution networks.

Degree: PhD, 2017, University of Manchester

URL: https://www.research.manchester.ac.uk/portal/en/theses/reliability-and-risk-analysis-of-post-fault-capacity-services-in-smart-distribution-networks(b1a93b49-d307-4561-800d-0a9944a7a577).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713616

► Recent technological developments are bringing about substantial changes that are converting traditional distribution networks into "smart" distribution networks. In particular, it is possible to observe…
(more)

Subjects/Keywords: 621.31; demand response; distribution network planning; differentiated reliability; distributed energy resources; sequential Monte Carlo simulation

Record Details Similar Records

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

APA (6^{th} Edition):

Syrri, A. L. A. (2017). Reliability and risk analysis of post fault capacity services in smart distribution networks. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/reliability-and-risk-analysis-of-post-fault-capacity-services-in-smart-distribution-networks(b1a93b49-d307-4561-800d-0a9944a7a577).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713616

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

Syrri, Angeliki Lydia Antonia. “Reliability and risk analysis of post fault capacity services in smart distribution networks.” 2017. Doctoral Dissertation, University of Manchester. Accessed June 25, 2019. https://www.research.manchester.ac.uk/portal/en/theses/reliability-and-risk-analysis-of-post-fault-capacity-services-in-smart-distribution-networks(b1a93b49-d307-4561-800d-0a9944a7a577).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713616.

MLA Handbook (7^{th} Edition):

Syrri, Angeliki Lydia Antonia. “Reliability and risk analysis of post fault capacity services in smart distribution networks.” 2017. Web. 25 Jun 2019.

Vancouver:

Syrri ALA. Reliability and risk analysis of post fault capacity services in smart distribution networks. [Internet] [Doctoral dissertation]. University of Manchester; 2017. [cited 2019 Jun 25]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/reliability-and-risk-analysis-of-post-fault-capacity-services-in-smart-distribution-networks(b1a93b49-d307-4561-800d-0a9944a7a577).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713616.

Council of Science Editors:

Syrri ALA. Reliability and risk analysis of post fault capacity services in smart distribution networks. [Doctoral Dissertation]. University of Manchester; 2017. Available from: https://www.research.manchester.ac.uk/portal/en/theses/reliability-and-risk-analysis-of-post-fault-capacity-services-in-smart-distribution-networks(b1a93b49-d307-4561-800d-0a9944a7a577).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.713616