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You searched for subject:(mixture models). Showing records 1 – 30 of 406 total matches.

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1. Pagani Zanini, Carlos Tadeu. Dependent mixtures and random partitions.

Degree: PhD, Statistics, 2019, University of Texas – Austin

 This work develops new methodology for Bayesian dependent mixture models and dependent random partitions with applications to biomedical data. A mixture model implies a random… (more)

Subjects/Keywords: Dependent mixture models; Bayesian models

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APA (6th Edition):

Pagani Zanini, C. T. (2019). Dependent mixtures and random partitions. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/3274

Chicago Manual of Style (16th Edition):

Pagani Zanini, Carlos Tadeu. “Dependent mixtures and random partitions.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed April 23, 2021. http://dx.doi.org/10.26153/tsw/3274.

MLA Handbook (7th Edition):

Pagani Zanini, Carlos Tadeu. “Dependent mixtures and random partitions.” 2019. Web. 23 Apr 2021.

Vancouver:

Pagani Zanini CT. Dependent mixtures and random partitions. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Apr 23]. Available from: http://dx.doi.org/10.26153/tsw/3274.

Council of Science Editors:

Pagani Zanini CT. Dependent mixtures and random partitions. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/3274


University of Texas – Austin

2. Tuggle, Kirsten Elizabeth. Model selection for Gaussian mixture model filtering and sensor scheduling.

Degree: PhD, Aerospace Engineering, 2020, University of Texas – Austin

 The use of Gaussian mixture model representations for nonlinear estimation is an attractive tool for object tracking and orbit determination. It is the potential for… (more)

Subjects/Keywords: Gaussian mixture models; Sensor scheduling

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APA (6th Edition):

Tuggle, K. E. (2020). Model selection for Gaussian mixture model filtering and sensor scheduling. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/9892

Chicago Manual of Style (16th Edition):

Tuggle, Kirsten Elizabeth. “Model selection for Gaussian mixture model filtering and sensor scheduling.” 2020. Doctoral Dissertation, University of Texas – Austin. Accessed April 23, 2021. http://dx.doi.org/10.26153/tsw/9892.

MLA Handbook (7th Edition):

Tuggle, Kirsten Elizabeth. “Model selection for Gaussian mixture model filtering and sensor scheduling.” 2020. Web. 23 Apr 2021.

Vancouver:

Tuggle KE. Model selection for Gaussian mixture model filtering and sensor scheduling. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2020. [cited 2021 Apr 23]. Available from: http://dx.doi.org/10.26153/tsw/9892.

Council of Science Editors:

Tuggle KE. Model selection for Gaussian mixture model filtering and sensor scheduling. [Doctoral Dissertation]. University of Texas – Austin; 2020. Available from: http://dx.doi.org/10.26153/tsw/9892


University of New South Wales

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

Degree: Economics, 2011, University of New South Wales

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

Subjects/Keywords: MCMC; Bayesian; Mixture models

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Pullen, James. “A Bayesian approach to mixture models and transdimensional Markov chains.” 2011. Doctoral Dissertation, University of New South Wales. Accessed April 23, 2021. http://handle.unsw.edu.au/1959.4/51520 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10207/SOURCE02?view=true.

MLA Handbook (7th Edition):

Pullen, James. “A Bayesian approach to mixture models and transdimensional Markov chains.” 2011. Web. 23 Apr 2021.

Vancouver:

Pullen J. A Bayesian approach to mixture models and transdimensional Markov chains. [Internet] [Doctoral dissertation]. University of New South Wales; 2011. [cited 2021 Apr 23]. Available from: http://handle.unsw.edu.au/1959.4/51520 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10207/SOURCE02?view=true.

Council of Science Editors:

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


Vanderbilt University

4. Rights, Jason Douglas. The relationship between multilevel models and nonparametric multilevel mixture models.

Degree: MS, Psychology, 2015, Vanderbilt University

 Multilevel data structures are common in the social sciences. Often, such nested data are analyzed with multilevel models (MLMs) wherein heterogeneity between clusters is modeled… (more)

Subjects/Keywords: nonparametric multilevel mixture models; multilevel models

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APA (6th Edition):

Rights, J. D. (2015). The relationship between multilevel models and nonparametric multilevel mixture models. (Thesis). Vanderbilt University. Retrieved from http://hdl.handle.net/1803/14436

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):

Rights, Jason Douglas. “The relationship between multilevel models and nonparametric multilevel mixture models.” 2015. Thesis, Vanderbilt University. Accessed April 23, 2021. http://hdl.handle.net/1803/14436.

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

MLA Handbook (7th Edition):

Rights, Jason Douglas. “The relationship between multilevel models and nonparametric multilevel mixture models.” 2015. Web. 23 Apr 2021.

Vancouver:

Rights JD. The relationship between multilevel models and nonparametric multilevel mixture models. [Internet] [Thesis]. Vanderbilt University; 2015. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/1803/14436.

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

Council of Science Editors:

Rights JD. The relationship between multilevel models and nonparametric multilevel mixture models. [Thesis]. Vanderbilt University; 2015. Available from: http://hdl.handle.net/1803/14436

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


Virginia Tech

5. Estejab, Bahareh. Hydrodynamic and gasification behavior of coal and biomass fluidized beds and their mixtures.

Degree: PhD, Mechanical Engineering, 2016, Virginia Tech

 In this study, efforts ensued to increase our knowledge of fluidization and gasification behavior of Geldart A particles using CFD. An extensive Eulerian-Eulerian numerical study… (more)

Subjects/Keywords: Biomass; Binary mixture; Coal; Drag models; Fluidization; Gasification; Co-gasification; Mixture

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APA (6th Edition):

Estejab, B. (2016). Hydrodynamic and gasification behavior of coal and biomass fluidized beds and their mixtures. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/79366

Chicago Manual of Style (16th Edition):

Estejab, Bahareh. “Hydrodynamic and gasification behavior of coal and biomass fluidized beds and their mixtures.” 2016. Doctoral Dissertation, Virginia Tech. Accessed April 23, 2021. http://hdl.handle.net/10919/79366.

MLA Handbook (7th Edition):

Estejab, Bahareh. “Hydrodynamic and gasification behavior of coal and biomass fluidized beds and their mixtures.” 2016. Web. 23 Apr 2021.

Vancouver:

Estejab B. Hydrodynamic and gasification behavior of coal and biomass fluidized beds and their mixtures. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/10919/79366.

Council of Science Editors:

Estejab B. Hydrodynamic and gasification behavior of coal and biomass fluidized beds and their mixtures. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/79366


McMaster University

6. Zhang, Xu Xuan. Non-Gaussian Mixture Model Averaging for Clustering.

Degree: MSc, 2016, McMaster University

The Gaussian mixture model has been used for model-based clustering analysis for decades. Most model-based clustering analyses are based on the Gaussian mixture model. Model… (more)

Subjects/Keywords: Model-based Clustering; Model Averaging; Mixture Models

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APA (6th Edition):

Zhang, X. X. (2016). Non-Gaussian Mixture Model Averaging for Clustering. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/20792

Chicago Manual of Style (16th Edition):

Zhang, Xu Xuan. “Non-Gaussian Mixture Model Averaging for Clustering.” 2016. Masters Thesis, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/20792.

MLA Handbook (7th Edition):

Zhang, Xu Xuan. “Non-Gaussian Mixture Model Averaging for Clustering.” 2016. Web. 23 Apr 2021.

Vancouver:

Zhang XX. Non-Gaussian Mixture Model Averaging for Clustering. [Internet] [Masters thesis]. McMaster University; 2016. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/20792.

Council of Science Editors:

Zhang XX. Non-Gaussian Mixture Model Averaging for Clustering. [Masters Thesis]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/20792


McMaster University

7. Tait, Peter A. Clustering Matrix Variate Data Using Finite Mixture Models with Component-Wise Regularization.

Degree: MSc, 2017, McMaster University

Matrix variate distributions present a innate way to model random matrices. Realiza- tions of random matrices are created by concurrently observing variables in different locations… (more)

Subjects/Keywords: Mixture models; Matrix variate distributions; Accelerometers; Pediatrics

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APA (6th Edition):

Tait, P. A. (2017). Clustering Matrix Variate Data Using Finite Mixture Models with Component-Wise Regularization. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/22133

Chicago Manual of Style (16th Edition):

Tait, Peter A. “Clustering Matrix Variate Data Using Finite Mixture Models with Component-Wise Regularization.” 2017. Masters Thesis, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/22133.

MLA Handbook (7th Edition):

Tait, Peter A. “Clustering Matrix Variate Data Using Finite Mixture Models with Component-Wise Regularization.” 2017. Web. 23 Apr 2021.

Vancouver:

Tait PA. Clustering Matrix Variate Data Using Finite Mixture Models with Component-Wise Regularization. [Internet] [Masters thesis]. McMaster University; 2017. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/22133.

Council of Science Editors:

Tait PA. Clustering Matrix Variate Data Using Finite Mixture Models with Component-Wise Regularization. [Masters Thesis]. McMaster University; 2017. Available from: http://hdl.handle.net/11375/22133


McMaster University

8. Gallaugher, Michael Patrick Brian. Analysis of Three-Way Data and Other Topics in Clustering and Classification.

Degree: PhD, 2020, McMaster University

Clustering and classification is the process of finding underlying group structure in heterogenous data. With the rise of the “big data” phenomenon, more complex data… (more)

Subjects/Keywords: clustering; classification; mixture models; matrix variate distributions

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APA (6th Edition):

Gallaugher, M. P. B. (2020). Analysis of Three-Way Data and Other Topics in Clustering and Classification. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/25359

Chicago Manual of Style (16th Edition):

Gallaugher, Michael Patrick Brian. “Analysis of Three-Way Data and Other Topics in Clustering and Classification.” 2020. Doctoral Dissertation, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/25359.

MLA Handbook (7th Edition):

Gallaugher, Michael Patrick Brian. “Analysis of Three-Way Data and Other Topics in Clustering and Classification.” 2020. Web. 23 Apr 2021.

Vancouver:

Gallaugher MPB. Analysis of Three-Way Data and Other Topics in Clustering and Classification. [Internet] [Doctoral dissertation]. McMaster University; 2020. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/25359.

Council of Science Editors:

Gallaugher MPB. Analysis of Three-Way Data and Other Topics in Clustering and Classification. [Doctoral Dissertation]. McMaster University; 2020. Available from: http://hdl.handle.net/11375/25359


McMaster University

9. Clark, Katharine. Outlier Detection in Gaussian Mixture Models.

Degree: MSc, 2020, McMaster University

Unsupervised classification is a problem often plagued by outliers, yet there is a paucity of work on handling outliers in unsupervised classification. Mixtures of Gaussian… (more)

Subjects/Keywords: clustering; outliers; model selection; mixture models

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APA (6th Edition):

Clark, K. (2020). Outlier Detection in Gaussian Mixture Models. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/25930

Chicago Manual of Style (16th Edition):

Clark, Katharine. “Outlier Detection in Gaussian Mixture Models.” 2020. Masters Thesis, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/25930.

MLA Handbook (7th Edition):

Clark, Katharine. “Outlier Detection in Gaussian Mixture Models.” 2020. Web. 23 Apr 2021.

Vancouver:

Clark K. Outlier Detection in Gaussian Mixture Models. [Internet] [Masters thesis]. McMaster University; 2020. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/25930.

Council of Science Editors:

Clark K. Outlier Detection in Gaussian Mixture Models. [Masters Thesis]. McMaster University; 2020. Available from: http://hdl.handle.net/11375/25930


University of Manchester

10. Brown, Liam John. General Blending Models for Mixture Experiments: Design and Analysis.

Degree: 2014, University of Manchester

It is felt the position of the Scheffé polynomials as the primary, or sometimes sole recourse for practitioners of mixture experiments leads to a lack… (more)

Subjects/Keywords: Mixture Experiments; Design of Experiments; Nonlinear Models

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APA (6th Edition):

Brown, L. J. (2014). General Blending Models for Mixture Experiments: Design and Analysis. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:222351

Chicago Manual of Style (16th Edition):

Brown, Liam John. “General Blending Models for Mixture Experiments: Design and Analysis.” 2014. Doctoral Dissertation, University of Manchester. Accessed April 23, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:222351.

MLA Handbook (7th Edition):

Brown, Liam John. “General Blending Models for Mixture Experiments: Design and Analysis.” 2014. Web. 23 Apr 2021.

Vancouver:

Brown LJ. General Blending Models for Mixture Experiments: Design and Analysis. [Internet] [Doctoral dissertation]. University of Manchester; 2014. [cited 2021 Apr 23]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:222351.

Council of Science Editors:

Brown LJ. General Blending Models for Mixture Experiments: Design and Analysis. [Doctoral Dissertation]. University of Manchester; 2014. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:222351


University of Waterloo

11. Maroufy, Vahed. Applications of Geometry in Optimization and Statistical Estimation.

Degree: 2016, University of Waterloo

 Geometric properties of statistical models and their influence on statistical inference and asymptotic theory reveal the profound relationship between geometry and statistics. This thesis studies… (more)

Subjects/Keywords: Convex and Differential Geometry; Mixture models; Local Mixture Models; Frailty survival models; Bayesian robustness; Computing Boundaries

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APA (6th Edition):

Maroufy, V. (2016). Applications of Geometry in Optimization and Statistical Estimation. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/10220

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):

Maroufy, Vahed. “Applications of Geometry in Optimization and Statistical Estimation.” 2016. Thesis, University of Waterloo. Accessed April 23, 2021. http://hdl.handle.net/10012/10220.

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

MLA Handbook (7th Edition):

Maroufy, Vahed. “Applications of Geometry in Optimization and Statistical Estimation.” 2016. Web. 23 Apr 2021.

Vancouver:

Maroufy V. Applications of Geometry in Optimization and Statistical Estimation. [Internet] [Thesis]. University of Waterloo; 2016. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/10012/10220.

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

Council of Science Editors:

Maroufy V. Applications of Geometry in Optimization and Statistical Estimation. [Thesis]. University of Waterloo; 2016. Available from: http://hdl.handle.net/10012/10220

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


Texas A&M University

12. Talluri, Rajesh. Bayesian Gaussian Graphical models using sparse selection priors and their mixtures.

Degree: PhD, Statistics, 2012, Texas A&M University

 We propose Bayesian methods for estimating the precision matrix in Gaussian graphical models. The methods lead to sparse and adaptively shrunk estimators of the precision… (more)

Subjects/Keywords: Bayesian; Gaussian Graphical Models; Covariance Selection; Mixture Models

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APA (6th Edition):

Talluri, R. (2012). Bayesian Gaussian Graphical models using sparse selection priors and their mixtures. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828

Chicago Manual of Style (16th Edition):

Talluri, Rajesh. “Bayesian Gaussian Graphical models using sparse selection priors and their mixtures.” 2012. Doctoral Dissertation, Texas A&M University. Accessed April 23, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828.

MLA Handbook (7th Edition):

Talluri, Rajesh. “Bayesian Gaussian Graphical models using sparse selection priors and their mixtures.” 2012. Web. 23 Apr 2021.

Vancouver:

Talluri R. Bayesian Gaussian Graphical models using sparse selection priors and their mixtures. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828.

Council of Science Editors:

Talluri R. Bayesian Gaussian Graphical models using sparse selection priors and their mixtures. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828


University of Waikato

13. Rohan, Maheswaran. Using Finite Mixtures to Robustify Statistical Models .

Degree: 2011, University of Waikato

 Abstract This thesis is concerned with robust estimation of the parameters of statistical models. Although robust estimation is a very good idea, it has some… (more)

Subjects/Keywords: Robust Statistics; Mixture Models; Statistical Models; EM Algorithm

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APA (6th Edition):

Rohan, M. (2011). Using Finite Mixtures to Robustify Statistical Models . (Doctoral Dissertation). University of Waikato. Retrieved from http://hdl.handle.net/10289/5110

Chicago Manual of Style (16th Edition):

Rohan, Maheswaran. “Using Finite Mixtures to Robustify Statistical Models .” 2011. Doctoral Dissertation, University of Waikato. Accessed April 23, 2021. http://hdl.handle.net/10289/5110.

MLA Handbook (7th Edition):

Rohan, Maheswaran. “Using Finite Mixtures to Robustify Statistical Models .” 2011. Web. 23 Apr 2021.

Vancouver:

Rohan M. Using Finite Mixtures to Robustify Statistical Models . [Internet] [Doctoral dissertation]. University of Waikato; 2011. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/10289/5110.

Council of Science Editors:

Rohan M. Using Finite Mixtures to Robustify Statistical Models . [Doctoral Dissertation]. University of Waikato; 2011. Available from: http://hdl.handle.net/10289/5110


East Tennessee State University

14. Pfister, Mark. Distribution of a Sum of Random Variables when the Sample Size is a Poisson Distribution.

Degree: MS, Mathematical Sciences, 2018, East Tennessee State University

  A probability distribution is a statistical function that describes the probability of possible outcomes in an experiment or occurrence. There are many different probability… (more)

Subjects/Keywords: Hierarchical Models; Mixture; Poisson; Probability Mass Function; Probability; Statistical Models

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APA (6th Edition):

Pfister, M. (2018). Distribution of a Sum of Random Variables when the Sample Size is a Poisson Distribution. (Thesis). East Tennessee State University. Retrieved from https://dc.etsu.edu/etd/3459

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):

Pfister, Mark. “Distribution of a Sum of Random Variables when the Sample Size is a Poisson Distribution.” 2018. Thesis, East Tennessee State University. Accessed April 23, 2021. https://dc.etsu.edu/etd/3459.

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

MLA Handbook (7th Edition):

Pfister, Mark. “Distribution of a Sum of Random Variables when the Sample Size is a Poisson Distribution.” 2018. Web. 23 Apr 2021.

Vancouver:

Pfister M. Distribution of a Sum of Random Variables when the Sample Size is a Poisson Distribution. [Internet] [Thesis]. East Tennessee State University; 2018. [cited 2021 Apr 23]. Available from: https://dc.etsu.edu/etd/3459.

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

Council of Science Editors:

Pfister M. Distribution of a Sum of Random Variables when the Sample Size is a Poisson Distribution. [Thesis]. East Tennessee State University; 2018. Available from: https://dc.etsu.edu/etd/3459

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

15. Huang, Zhiyue. The Generalized Method of Moments for Mixture and Mixed Models.

Degree: 2015, University of Waterloo

Mixture models can be found in a wide variety of statistical applications. However, undertaking statistical inference in mixture models, especially non-parametric mixture models, can be… (more)

Subjects/Keywords: Mixture Models; Mixed-effects Models; Generalized Method of Moments; Hypothesis Testing

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APA (6th Edition):

Huang, Z. (2015). The Generalized Method of Moments for Mixture and Mixed Models. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/9737

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):

Huang, Zhiyue. “The Generalized Method of Moments for Mixture and Mixed Models.” 2015. Thesis, University of Waterloo. Accessed April 23, 2021. http://hdl.handle.net/10012/9737.

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

MLA Handbook (7th Edition):

Huang, Zhiyue. “The Generalized Method of Moments for Mixture and Mixed Models.” 2015. Web. 23 Apr 2021.

Vancouver:

Huang Z. The Generalized Method of Moments for Mixture and Mixed Models. [Internet] [Thesis]. University of Waterloo; 2015. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/10012/9737.

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

Council of Science Editors:

Huang Z. The Generalized Method of Moments for Mixture and Mixed Models. [Thesis]. University of Waterloo; 2015. Available from: http://hdl.handle.net/10012/9737

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


McMaster University

16. Wei, Yuhong. Extending Growth Mixture Models and Handling Missing Values via Mixtures of Non-Elliptical Distributions.

Degree: PhD, 2017, McMaster University

Growth mixture models (GMMs) are used to model intra-individual change and inter-individual differences in change and to detect underlying group structure in longitudinal studies. Regularly,… (more)

Subjects/Keywords: Growth Mixture Model; Model-Based Clustering; EM Algorithm; Missing Data; Finite Mixture Models

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APA (6th Edition):

Wei, Y. (2017). Extending Growth Mixture Models and Handling Missing Values via Mixtures of Non-Elliptical Distributions. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/21987

Chicago Manual of Style (16th Edition):

Wei, Yuhong. “Extending Growth Mixture Models and Handling Missing Values via Mixtures of Non-Elliptical Distributions.” 2017. Doctoral Dissertation, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/21987.

MLA Handbook (7th Edition):

Wei, Yuhong. “Extending Growth Mixture Models and Handling Missing Values via Mixtures of Non-Elliptical Distributions.” 2017. Web. 23 Apr 2021.

Vancouver:

Wei Y. Extending Growth Mixture Models and Handling Missing Values via Mixtures of Non-Elliptical Distributions. [Internet] [Doctoral dissertation]. McMaster University; 2017. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/21987.

Council of Science Editors:

Wei Y. Extending Growth Mixture Models and Handling Missing Values via Mixtures of Non-Elliptical Distributions. [Doctoral Dissertation]. McMaster University; 2017. Available from: http://hdl.handle.net/11375/21987

17. Dijk, Bram. Essays on Finite Mixture Models.

Degree: 2009, Erasmus School of Economics

 textabstractFinite mixture distributions are a weighted average of a ¯nite number of distributions. The latter are usually called the mixture components. The weights are usually… (more)

Subjects/Keywords: finite mixture distribution; finite mixture models

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APA (6th Edition):

Dijk, B. (2009). Essays on Finite Mixture Models. (Doctoral Dissertation). Erasmus School of Economics. Retrieved from http://hdl.handle.net/1765/16185

Chicago Manual of Style (16th Edition):

Dijk, Bram. “Essays on Finite Mixture Models.” 2009. Doctoral Dissertation, Erasmus School of Economics. Accessed April 23, 2021. http://hdl.handle.net/1765/16185.

MLA Handbook (7th Edition):

Dijk, Bram. “Essays on Finite Mixture Models.” 2009. Web. 23 Apr 2021.

Vancouver:

Dijk B. Essays on Finite Mixture Models. [Internet] [Doctoral dissertation]. Erasmus School of Economics; 2009. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/1765/16185.

Council of Science Editors:

Dijk B. Essays on Finite Mixture Models. [Doctoral Dissertation]. Erasmus School of Economics; 2009. Available from: http://hdl.handle.net/1765/16185

18. Priya,P Menon. Some concepts and models usefulninthe analysis of discrete life time data.

Degree: Statistics, 2013, Cochin University of Science and Technology

This thesis entitled Reliability Modelling and Analysis in Discrete time Some Concepts and Models Useful in the Analysis of discrete life time data.The present study… (more)

Subjects/Keywords: Reliability models in discrete time; Basic reliability concepts; Mixture models; Partial moments; Geometric mixture; Modelling lifetime data

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APA (6th Edition):

Menon, P. (2013). Some concepts and models usefulninthe analysis of discrete life time data. (Thesis). Cochin University of Science and Technology. Retrieved from http://dyuthi.cusat.ac.in/purl/3095

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):

Menon, Priya,P. “Some concepts and models usefulninthe analysis of discrete life time data.” 2013. Thesis, Cochin University of Science and Technology. Accessed April 23, 2021. http://dyuthi.cusat.ac.in/purl/3095.

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

MLA Handbook (7th Edition):

Menon, Priya,P. “Some concepts and models usefulninthe analysis of discrete life time data.” 2013. Web. 23 Apr 2021.

Vancouver:

Menon P. Some concepts and models usefulninthe analysis of discrete life time data. [Internet] [Thesis]. Cochin University of Science and Technology; 2013. [cited 2021 Apr 23]. Available from: http://dyuthi.cusat.ac.in/purl/3095.

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

Council of Science Editors:

Menon P. Some concepts and models usefulninthe analysis of discrete life time data. [Thesis]. Cochin University of Science and Technology; 2013. Available from: http://dyuthi.cusat.ac.in/purl/3095

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


University of California – Irvine

19. Ozcan, Fulya. Bayesian Nonparametric Models on Big Data.

Degree: Economics, 2017, University of California – Irvine

 This thesis focuses on the role investor type and sentiment play in financial markets, using data from social media. First paper investigates the effect of… (more)

Subjects/Keywords: Economics; Statistics; Computer science; Dirichlet Mixture Models; Exchange Rate Prediction; Hidden Network Discovery; Hiearchical Mixture Models; Natural Language Processing; Overlapping Communities

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APA (6th Edition):

Ozcan, F. (2017). Bayesian Nonparametric Models on Big Data. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/2qh0w0n8

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):

Ozcan, Fulya. “Bayesian Nonparametric Models on Big Data.” 2017. Thesis, University of California – Irvine. Accessed April 23, 2021. http://www.escholarship.org/uc/item/2qh0w0n8.

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

MLA Handbook (7th Edition):

Ozcan, Fulya. “Bayesian Nonparametric Models on Big Data.” 2017. Web. 23 Apr 2021.

Vancouver:

Ozcan F. Bayesian Nonparametric Models on Big Data. [Internet] [Thesis]. University of California – Irvine; 2017. [cited 2021 Apr 23]. Available from: http://www.escholarship.org/uc/item/2qh0w0n8.

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

Council of Science Editors:

Ozcan F. Bayesian Nonparametric Models on Big Data. [Thesis]. University of California – Irvine; 2017. Available from: http://www.escholarship.org/uc/item/2qh0w0n8

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


University of Georgia

20. Choi, Hye-Jeong. A model that combines diagnostic classification assessment with mixture item response theory models.

Degree: 2014, University of Georgia

 The purpose of this dissertation is to present a new psychometric model that combines a Mixture Rasch model with a diagnostic model. We refer to… (more)

Subjects/Keywords: Local dependence; Multidimensionality; Latent class model; Mixture Rasch model; Diagnostic models; Log-linear cognitive diagnosis models; Diagnostic classification mixture Rasch model

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

APA (6th Edition):

Choi, H. (2014). A model that combines diagnostic classification assessment with mixture item response theory models. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/26276

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):

Choi, Hye-Jeong. “A model that combines diagnostic classification assessment with mixture item response theory models.” 2014. Thesis, University of Georgia. Accessed April 23, 2021. http://hdl.handle.net/10724/26276.

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

MLA Handbook (7th Edition):

Choi, Hye-Jeong. “A model that combines diagnostic classification assessment with mixture item response theory models.” 2014. Web. 23 Apr 2021.

Vancouver:

Choi H. A model that combines diagnostic classification assessment with mixture item response theory models. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/10724/26276.

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

Council of Science Editors:

Choi H. A model that combines diagnostic classification assessment with mixture item response theory models. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/26276

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


Rochester Institute of Technology

21. Bowen, Ryan M. Online Novelty Detection System: One-Class Classification of Systemic Operation.

Degree: PhD, Microsystems Engineering, 2016, Rochester Institute of Technology

  Presented is an Online Novelty Detection System (ONDS) that uses Gaussian Mixture Models (GMMs) and one-class classification techniques to identify novel information from multivariate… (more)

Subjects/Keywords: Gaussian mixture models; Novelty detection; One-class classification

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

APA (6th Edition):

Bowen, R. M. (2016). Online Novelty Detection System: One-Class Classification of Systemic Operation. (Doctoral Dissertation). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/8944

Chicago Manual of Style (16th Edition):

Bowen, Ryan M. “Online Novelty Detection System: One-Class Classification of Systemic Operation.” 2016. Doctoral Dissertation, Rochester Institute of Technology. Accessed April 23, 2021. https://scholarworks.rit.edu/theses/8944.

MLA Handbook (7th Edition):

Bowen, Ryan M. “Online Novelty Detection System: One-Class Classification of Systemic Operation.” 2016. Web. 23 Apr 2021.

Vancouver:

Bowen RM. Online Novelty Detection System: One-Class Classification of Systemic Operation. [Internet] [Doctoral dissertation]. Rochester Institute of Technology; 2016. [cited 2021 Apr 23]. Available from: https://scholarworks.rit.edu/theses/8944.

Council of Science Editors:

Bowen RM. Online Novelty Detection System: One-Class Classification of Systemic Operation. [Doctoral Dissertation]. Rochester Institute of Technology; 2016. Available from: https://scholarworks.rit.edu/theses/8944

22. Karavasilis, Vasileios. Visual tracking in image sequences using mixture models.

Degree: 2015, University of Ioannina; Πανεπιστήμιο Ιωαννίνων

This thesis solves the problem of visual tracking in image sequences, which is a computer visions subfield. To solve this problem, mixture models of various… (more)

Subjects/Keywords: Εικονοσειρές; Εκτίμηση κίνησης; Μικτές κατανομές; Image sequences; Visual tracking; Mixture models

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

APA (6th Edition):

Karavasilis, V. (2015). Visual tracking in image sequences using mixture models. (Thesis). University of Ioannina; Πανεπιστήμιο Ιωαννίνων. Retrieved from http://hdl.handle.net/10442/hedi/43023

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):

Karavasilis, Vasileios. “Visual tracking in image sequences using mixture models.” 2015. Thesis, University of Ioannina; Πανεπιστήμιο Ιωαννίνων. Accessed April 23, 2021. http://hdl.handle.net/10442/hedi/43023.

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

MLA Handbook (7th Edition):

Karavasilis, Vasileios. “Visual tracking in image sequences using mixture models.” 2015. Web. 23 Apr 2021.

Vancouver:

Karavasilis V. Visual tracking in image sequences using mixture models. [Internet] [Thesis]. University of Ioannina; Πανεπιστήμιο Ιωαννίνων; 2015. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/10442/hedi/43023.

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

Council of Science Editors:

Karavasilis V. Visual tracking in image sequences using mixture models. [Thesis]. University of Ioannina; Πανεπιστήμιο Ιωαννίνων; 2015. Available from: http://hdl.handle.net/10442/hedi/43023

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


Penn State University

23. Abar, Beau. Beyond Population Level Effects: Addressing Sample Heterogeneity in Prevention Research .

Degree: 2010, Penn State University

 The unifying theme of my three-paper dissertation was the examination of interindividual differences using two general methods for illustrating heterogeneity in a sample: mixture models(more)

Subjects/Keywords: mixture models; prevention; skin cancer

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

APA (6th Edition):

Abar, B. (2010). Beyond Population Level Effects: Addressing Sample Heterogeneity in Prevention Research . (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/11077

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):

Abar, Beau. “Beyond Population Level Effects: Addressing Sample Heterogeneity in Prevention Research .” 2010. Thesis, Penn State University. Accessed April 23, 2021. https://submit-etda.libraries.psu.edu/catalog/11077.

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

MLA Handbook (7th Edition):

Abar, Beau. “Beyond Population Level Effects: Addressing Sample Heterogeneity in Prevention Research .” 2010. Web. 23 Apr 2021.

Vancouver:

Abar B. Beyond Population Level Effects: Addressing Sample Heterogeneity in Prevention Research . [Internet] [Thesis]. Penn State University; 2010. [cited 2021 Apr 23]. Available from: https://submit-etda.libraries.psu.edu/catalog/11077.

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

Council of Science Editors:

Abar B. Beyond Population Level Effects: Addressing Sample Heterogeneity in Prevention Research . [Thesis]. Penn State University; 2010. Available from: https://submit-etda.libraries.psu.edu/catalog/11077

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


Texas A&M University

24. Liu, Guannan. Forecasting Financial Returns: A Copula-Based Method and a Robust Test.

Degree: PhD, Economics, 2016, Texas A&M University

 My dissertation includes two essays studying the forecasting of financial returns. In the first essay, I study the temporal dependence structures of financial returns by… (more)

Subjects/Keywords: Copula; Mixture copula; Model average; Nonlinear Markov models; Orthogonality test

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APA (6th Edition):

Liu, G. (2016). Forecasting Financial Returns: A Copula-Based Method and a Robust Test. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/156914

Chicago Manual of Style (16th Edition):

Liu, Guannan. “Forecasting Financial Returns: A Copula-Based Method and a Robust Test.” 2016. Doctoral Dissertation, Texas A&M University. Accessed April 23, 2021. http://hdl.handle.net/1969.1/156914.

MLA Handbook (7th Edition):

Liu, Guannan. “Forecasting Financial Returns: A Copula-Based Method and a Robust Test.” 2016. Web. 23 Apr 2021.

Vancouver:

Liu G. Forecasting Financial Returns: A Copula-Based Method and a Robust Test. [Internet] [Doctoral dissertation]. Texas A&M University; 2016. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/1969.1/156914.

Council of Science Editors:

Liu G. Forecasting Financial Returns: A Copula-Based Method and a Robust Test. [Doctoral Dissertation]. Texas A&M University; 2016. Available from: http://hdl.handle.net/1969.1/156914


Texas A&M University

25. Taha, Mohamed Ahmed. On The Chemical Mixture Methodologies for Estimation of the Integrated Health Effects.

Degree: MS, Chemical Engineering, 2014, Texas A&M University

 It is very worthwhile for the regulatory agencies to have an understandable method to evaluate the health effects for humans who may be exposed to… (more)

Subjects/Keywords: Chemical mixture Methodology; health effects; dispersion models; AERMOD; emission factors

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APA (6th Edition):

Taha, M. A. (2014). On The Chemical Mixture Methodologies for Estimation of the Integrated Health Effects. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/153952

Chicago Manual of Style (16th Edition):

Taha, Mohamed Ahmed. “On The Chemical Mixture Methodologies for Estimation of the Integrated Health Effects.” 2014. Masters Thesis, Texas A&M University. Accessed April 23, 2021. http://hdl.handle.net/1969.1/153952.

MLA Handbook (7th Edition):

Taha, Mohamed Ahmed. “On The Chemical Mixture Methodologies for Estimation of the Integrated Health Effects.” 2014. Web. 23 Apr 2021.

Vancouver:

Taha MA. On The Chemical Mixture Methodologies for Estimation of the Integrated Health Effects. [Internet] [Masters thesis]. Texas A&M University; 2014. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/1969.1/153952.

Council of Science Editors:

Taha MA. On The Chemical Mixture Methodologies for Estimation of the Integrated Health Effects. [Masters Thesis]. Texas A&M University; 2014. Available from: http://hdl.handle.net/1969.1/153952


McMaster University

26. Patel, Nidhi. Longitudinal Clustering via Mixtures of Multivariate Power Exponential Distributions.

Degree: MSc, 2016, McMaster University

A mixture model approach for clustering longitudinal data is introduced. The approach, which is based on mixtures of multivariate power exponential distributions, allows for varying… (more)

Subjects/Keywords: longitudinal data; model-based clustering; mixture models; power exponential distribution

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APA (6th Edition):

Patel, N. (2016). Longitudinal Clustering via Mixtures of Multivariate Power Exponential Distributions. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/20406

Chicago Manual of Style (16th Edition):

Patel, Nidhi. “Longitudinal Clustering via Mixtures of Multivariate Power Exponential Distributions.” 2016. Masters Thesis, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/20406.

MLA Handbook (7th Edition):

Patel, Nidhi. “Longitudinal Clustering via Mixtures of Multivariate Power Exponential Distributions.” 2016. Web. 23 Apr 2021.

Vancouver:

Patel N. Longitudinal Clustering via Mixtures of Multivariate Power Exponential Distributions. [Internet] [Masters thesis]. McMaster University; 2016. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/20406.

Council of Science Editors:

Patel N. Longitudinal Clustering via Mixtures of Multivariate Power Exponential Distributions. [Masters Thesis]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/20406


McMaster University

27. Blostein, Martin. An Efficient Implementation of a Robust Clustering Algorithm.

Degree: MSc, 2016, McMaster University

Clustering and classification are fundamental problems in statistical and machine learning, with a broad range of applications. A common approach is the Gaussian mixture model,… (more)

Subjects/Keywords: clustering; classification; statistical learning; machine learning; robust; computational statistics; mixture models

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APA (6th Edition):

Blostein, M. (2016). An Efficient Implementation of a Robust Clustering Algorithm. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/20598

Chicago Manual of Style (16th Edition):

Blostein, Martin. “An Efficient Implementation of a Robust Clustering Algorithm.” 2016. Masters Thesis, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/20598.

MLA Handbook (7th Edition):

Blostein, Martin. “An Efficient Implementation of a Robust Clustering Algorithm.” 2016. Web. 23 Apr 2021.

Vancouver:

Blostein M. An Efficient Implementation of a Robust Clustering Algorithm. [Internet] [Masters thesis]. McMaster University; 2016. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/20598.

Council of Science Editors:

Blostein M. An Efficient Implementation of a Robust Clustering Algorithm. [Masters Thesis]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/20598


McMaster University

28. Gallaugher, Michael P.B. On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution.

Degree: MSc, 2016, McMaster University

Recent work on fractionally-supervised classification (FSC), an approach that allows classification to be carried out with a fractional amount of weight given to the unla-… (more)

Subjects/Keywords: Fractionally Supervised Classification; Clustering; Discriminant Analysis; Mixture Models

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APA (6th Edition):

Gallaugher, M. P. B. (2016). On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/20738

Chicago Manual of Style (16th Edition):

Gallaugher, Michael P B. “On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution.” 2016. Masters Thesis, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/20738.

MLA Handbook (7th Edition):

Gallaugher, Michael P B. “On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution.” 2016. Web. 23 Apr 2021.

Vancouver:

Gallaugher MPB. On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. [Internet] [Masters thesis]. McMaster University; 2016. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/20738.

Council of Science Editors:

Gallaugher MPB. On Fractionally-Supervised Classification: Weight Selection and Extension to the Multivariate t-Distribution. [Masters Thesis]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/20738


McMaster University

29. Wong, Monica. Topics in One-Way Supervised Biclustering Using Gaussian Mixture Models.

Degree: PhD, 2017, McMaster University

Cluster analysis identifies homogeneous groups that are relevant within a population. In model-based clustering, group membership is estimated using a parametric finite mixture model, commonly… (more)

Subjects/Keywords: Biclustering; One-way supervision; Finite mixture models; Model-based clustering

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

APA (6th Edition):

Wong, M. (2017). Topics in One-Way Supervised Biclustering Using Gaussian Mixture Models. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/21065

Chicago Manual of Style (16th Edition):

Wong, Monica. “Topics in One-Way Supervised Biclustering Using Gaussian Mixture Models.” 2017. Doctoral Dissertation, McMaster University. Accessed April 23, 2021. http://hdl.handle.net/11375/21065.

MLA Handbook (7th Edition):

Wong, Monica. “Topics in One-Way Supervised Biclustering Using Gaussian Mixture Models.” 2017. Web. 23 Apr 2021.

Vancouver:

Wong M. Topics in One-Way Supervised Biclustering Using Gaussian Mixture Models. [Internet] [Doctoral dissertation]. McMaster University; 2017. [cited 2021 Apr 23]. Available from: http://hdl.handle.net/11375/21065.

Council of Science Editors:

Wong M. Topics in One-Way Supervised Biclustering Using Gaussian Mixture Models. [Doctoral Dissertation]. McMaster University; 2017. Available from: http://hdl.handle.net/11375/21065


Penn State University

30. Kuruppumullage Don, Prabhani. Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach.

Degree: 2014, Penn State University

 Clustering is the task of finding useful and meaningful groups in data, in a way that members within a group are more similar to each… (more)

Subjects/Keywords: Block clustering; Composite Likelihood; EM algorithm; Mixture models

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APA (6th Edition):

Kuruppumullage Don, P. (2014). Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/22368

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):

Kuruppumullage Don, Prabhani. “Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach.” 2014. Thesis, Penn State University. Accessed April 23, 2021. https://submit-etda.libraries.psu.edu/catalog/22368.

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

MLA Handbook (7th Edition):

Kuruppumullage Don, Prabhani. “Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach.” 2014. Web. 23 Apr 2021.

Vancouver:

Kuruppumullage Don P. Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach. [Internet] [Thesis]. Penn State University; 2014. [cited 2021 Apr 23]. Available from: https://submit-etda.libraries.psu.edu/catalog/22368.

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

Council of Science Editors:

Kuruppumullage Don P. Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach. [Thesis]. Penn State University; 2014. Available from: https://submit-etda.libraries.psu.edu/catalog/22368

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

[1] [2] [3] [4] [5] … [14]

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