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406 total matches.

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- 2017 – 2021 (133)
- 2012 – 2016 (163)
- 2007 – 2011 (108)
- 2002 – 2006 (18)

Universities

- Penn State University (17)
- McMaster University (16)
- Texas A&M University (12)
- Brno University of Technology (11)
- University of Georgia (11)
- University of São Paulo (10)

Degrees

- PhD (98)
- Docteur es (35)
- MS (28)

Languages

- English (229)
- Portuguese (32)
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1. Pagani Zanini, Carlos Tadeu. Dependent mixtures and random partitions.

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

URL: http://dx.doi.org/10.26153/tsw/3274

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://dx.doi.org/10.26153/tsw/9892

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://handle.unsw.edu.au/1959.4/51520 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10207/SOURCE02?view=true

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

Subjects/Keywords: MCMC; Bayesian; Mixture models

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1803/14436

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

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

URL: http://hdl.handle.net/10919/79366

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11375/20792

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11375/22133

►

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11375/25359

►

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11375/25930

►

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:222351

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/10012/10220

► 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 (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2011-08-9828

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/10289/5110

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: https://dc.etsu.edu/etd/3459

► 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

Record Details Similar Records

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APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/10012/9737

► *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

Record Details Similar Records

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APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/11375/21987

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1765/16185

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://dyuthi.cusat.ac.in/purl/3095

►

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://www.escholarship.org/uc/item/2qh0w0n8

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

APA (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/10724/26276

► 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 (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: https://scholarworks.rit.edu/theses/8944

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/10442/hedi/43023

►

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 (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: https://submit-etda.libraries.psu.edu/catalog/11077

► 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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/1969.1/156914

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1969.1/153952

► 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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11375/20406

►

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11375/20598

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11375/20738

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11375/21065

►

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

Record Details Similar Records

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

APA (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: https://submit-etda.libraries.psu.edu/catalog/22368

► 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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

Not specified: Masters Thesis or Doctoral Dissertation