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You searched for subject:(EM algorithm). Showing records 1 – 30 of 260 total matches.

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1. Plasse, Joshua H. The EM Algorithm in Multivariate Gaussian Mixture Models using Anderson Acceleration.

Degree: MS, 2013, Worcester Polytechnic Institute

  Over the years analysts have used the EM algorithm to obtain maximum likelihood estimates from incomplete data for various models. The general algorithm admits… (more)

Subjects/Keywords: EM algorithm; Anderson acceleration

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APA (6th Edition):

Plasse, J. H. (2013). The EM Algorithm in Multivariate Gaussian Mixture Models using Anderson Acceleration. (Thesis). Worcester Polytechnic Institute. Retrieved from etd-042513-091152 ; https://digitalcommons.wpi.edu/etd-theses/290

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):

Plasse, Joshua H. “The EM Algorithm in Multivariate Gaussian Mixture Models using Anderson Acceleration.” 2013. Thesis, Worcester Polytechnic Institute. Accessed August 07, 2020. etd-042513-091152 ; https://digitalcommons.wpi.edu/etd-theses/290.

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

MLA Handbook (7th Edition):

Plasse, Joshua H. “The EM Algorithm in Multivariate Gaussian Mixture Models using Anderson Acceleration.” 2013. Web. 07 Aug 2020.

Vancouver:

Plasse JH. The EM Algorithm in Multivariate Gaussian Mixture Models using Anderson Acceleration. [Internet] [Thesis]. Worcester Polytechnic Institute; 2013. [cited 2020 Aug 07]. Available from: etd-042513-091152 ; https://digitalcommons.wpi.edu/etd-theses/290.

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

Council of Science Editors:

Plasse JH. The EM Algorithm in Multivariate Gaussian Mixture Models using Anderson Acceleration. [Thesis]. Worcester Polytechnic Institute; 2013. Available from: etd-042513-091152 ; https://digitalcommons.wpi.edu/etd-theses/290

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


Penn State University

2. Yang, Tao. An EM Based Tagging SNP Selection Algorithm Incorporating Genotyping Errors.

Degree: MS, Statistics, 2014, Penn State University

 Many tagging SNP selection methods depend heavily on the estimated haplotype frequencies. One limitation of the existing tagging SNP selection algorithms is that they assume… (more)

Subjects/Keywords: tagging SNP selection; EM algorithm; genotyping errors

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APA (6th Edition):

Yang, T. (2014). An EM Based Tagging SNP Selection Algorithm Incorporating Genotyping Errors. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/21780

Chicago Manual of Style (16th Edition):

Yang, Tao. “An EM Based Tagging SNP Selection Algorithm Incorporating Genotyping Errors.” 2014. Masters Thesis, Penn State University. Accessed August 07, 2020. https://etda.libraries.psu.edu/catalog/21780.

MLA Handbook (7th Edition):

Yang, Tao. “An EM Based Tagging SNP Selection Algorithm Incorporating Genotyping Errors.” 2014. Web. 07 Aug 2020.

Vancouver:

Yang T. An EM Based Tagging SNP Selection Algorithm Incorporating Genotyping Errors. [Internet] [Masters thesis]. Penn State University; 2014. [cited 2020 Aug 07]. Available from: https://etda.libraries.psu.edu/catalog/21780.

Council of Science Editors:

Yang T. An EM Based Tagging SNP Selection Algorithm Incorporating Genotyping Errors. [Masters Thesis]. Penn State University; 2014. Available from: https://etda.libraries.psu.edu/catalog/21780


University of Alberta

3. Deng,Jing. Modeling and Development of Soft Sensors with Particle Filtering Approach.

Degree: MS, Department of Chemical and Materials Engineering, 2012, University of Alberta

 Limitations of measurement techniques and increasingly complex chemical process render difficulties in obtaining certain critical process variables. The hardware sensor reading may have an obvious… (more)

Subjects/Keywords: EM algorithm; Particle Filter; Soft Sensor

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APA (6th Edition):

Deng,Jing. (2012). Modeling and Development of Soft Sensors with Particle Filtering Approach. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/k643b130g

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

Deng,Jing. “Modeling and Development of Soft Sensors with Particle Filtering Approach.” 2012. Masters Thesis, University of Alberta. Accessed August 07, 2020. https://era.library.ualberta.ca/files/k643b130g.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

Deng,Jing. “Modeling and Development of Soft Sensors with Particle Filtering Approach.” 2012. Web. 07 Aug 2020.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

Deng,Jing. Modeling and Development of Soft Sensors with Particle Filtering Approach. [Internet] [Masters thesis]. University of Alberta; 2012. [cited 2020 Aug 07]. Available from: https://era.library.ualberta.ca/files/k643b130g.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

Deng,Jing. Modeling and Development of Soft Sensors with Particle Filtering Approach. [Masters Thesis]. University of Alberta; 2012. Available from: https://era.library.ualberta.ca/files/k643b130g

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Alberta

4. Jin, Xing. Multiple ARX Model Based Identification for Switching/Nonlinear Systems with EM Algorithm.

Degree: MS, Department of Chemical and Materials Engineering, 2010, University of Alberta

 Two different types of switching mechanism are considered in this thesis; one is featured with abrupt/sudden switching while the other one shows gradual changing behavior… (more)

Subjects/Keywords: Switching Systems; System Identification; EM Algorithm

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APA (6th Edition):

Jin, X. (2010). Multiple ARX Model Based Identification for Switching/Nonlinear Systems with EM Algorithm. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/7p88ch465

Chicago Manual of Style (16th Edition):

Jin, Xing. “Multiple ARX Model Based Identification for Switching/Nonlinear Systems with EM Algorithm.” 2010. Masters Thesis, University of Alberta. Accessed August 07, 2020. https://era.library.ualberta.ca/files/7p88ch465.

MLA Handbook (7th Edition):

Jin, Xing. “Multiple ARX Model Based Identification for Switching/Nonlinear Systems with EM Algorithm.” 2010. Web. 07 Aug 2020.

Vancouver:

Jin X. Multiple ARX Model Based Identification for Switching/Nonlinear Systems with EM Algorithm. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2020 Aug 07]. Available from: https://era.library.ualberta.ca/files/7p88ch465.

Council of Science Editors:

Jin X. Multiple ARX Model Based Identification for Switching/Nonlinear Systems with EM Algorithm. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/7p88ch465


University of Illinois – Urbana-Champaign

5. Huang, Weihong. Statistical algorithms using multisets and statistical inference of heterogeneous networks.

Degree: PhD, Statistics, 2017, University of Illinois – Urbana-Champaign

 Computational statistics, including methods such as Markov chain Monte Carlo (MCMC), bootstrap, approximate Bayesian computation, is an important part in modern statistics and has been… (more)

Subjects/Keywords: Multisets; Expectation-maximization (EM) algorithm; Metropolis-Hastings algorithm; Heterogeneous network; Clustering; Mixed membership model; Variational algorithm

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APA (6th Edition):

Huang, W. (2017). Statistical algorithms using multisets and statistical inference of heterogeneous networks. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/98245

Chicago Manual of Style (16th Edition):

Huang, Weihong. “Statistical algorithms using multisets and statistical inference of heterogeneous networks.” 2017. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed August 07, 2020. http://hdl.handle.net/2142/98245.

MLA Handbook (7th Edition):

Huang, Weihong. “Statistical algorithms using multisets and statistical inference of heterogeneous networks.” 2017. Web. 07 Aug 2020.

Vancouver:

Huang W. Statistical algorithms using multisets and statistical inference of heterogeneous networks. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2142/98245.

Council of Science Editors:

Huang W. Statistical algorithms using multisets and statistical inference of heterogeneous networks. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2017. Available from: http://hdl.handle.net/2142/98245

6. Rosangela Aparecida Botinha AssumpÃÃo. InfluÃncia local em modelos geoestatÃsticos T-Student com aplicaÃÃes a dados agrÃcolas.

Degree: 2010, Universidade Estadual do Oeste do Parana

A presenÃa de observaÃÃes discrepantes torna imprÃpria a anÃlise do processo gaussiano, sendo assim, como à encontrado na literatura, esse processo deve ser substituÃdo por… (more)

Subjects/Keywords: GeoestatÃstica; Algoritmo EM; MÃxima verossimilhanÃa; Geostatistics; EM Algorithm; ENGENHARIA AGRICOLA; Maximum Likelihood

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APA (6th Edition):

AssumpÃÃo, R. A. B. (2010). InfluÃncia local em modelos geoestatÃsticos T-Student com aplicaÃÃes a dados agrÃcolas. (Thesis). Universidade Estadual do Oeste do Parana. Retrieved from http://tede.unioeste.br/tede//tde_busca/arquivo.php?codArquivo=802

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):

AssumpÃÃo, Rosangela Aparecida Botinha. “InfluÃncia local em modelos geoestatÃsticos T-Student com aplicaÃÃes a dados agrÃcolas.” 2010. Thesis, Universidade Estadual do Oeste do Parana. Accessed August 07, 2020. http://tede.unioeste.br/tede//tde_busca/arquivo.php?codArquivo=802.

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

MLA Handbook (7th Edition):

AssumpÃÃo, Rosangela Aparecida Botinha. “InfluÃncia local em modelos geoestatÃsticos T-Student com aplicaÃÃes a dados agrÃcolas.” 2010. Web. 07 Aug 2020.

Vancouver:

AssumpÃÃo RAB. InfluÃncia local em modelos geoestatÃsticos T-Student com aplicaÃÃes a dados agrÃcolas. [Internet] [Thesis]. Universidade Estadual do Oeste do Parana; 2010. [cited 2020 Aug 07]. Available from: http://tede.unioeste.br/tede//tde_busca/arquivo.php?codArquivo=802.

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

Council of Science Editors:

AssumpÃÃo RAB. InfluÃncia local em modelos geoestatÃsticos T-Student com aplicaÃÃes a dados agrÃcolas. [Thesis]. Universidade Estadual do Oeste do Parana; 2010. Available from: http://tede.unioeste.br/tede//tde_busca/arquivo.php?codArquivo=802

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


Penn State University

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

Degree: PhD, Statistics, 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. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/22368

Chicago Manual of Style (16th Edition):

Kuruppumullage Don, Prabhani. “Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach.” 2014. Doctoral Dissertation, Penn State University. Accessed August 07, 2020. https://etda.libraries.psu.edu/catalog/22368.

MLA Handbook (7th Edition):

Kuruppumullage Don, Prabhani. “Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach.” 2014. Web. 07 Aug 2020.

Vancouver:

Kuruppumullage Don P. Estimation and Model Selection for Block Clustering with Mixtures: A Composite Likelihood Approach. [Internet] [Doctoral dissertation]. Penn State University; 2014. [cited 2020 Aug 07]. Available from: https://etda.libraries.psu.edu/catalog/22368.

Council of Science Editors:

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


Penn State University

8. Benaglia, Tatiana A. NONPARAMETRIC ESTIMATION IN MULTIVARIATE FINITE MIXTURE MODELS.

Degree: PhD, Statistics, 2008, Penn State University

 The main goal of this thesis is to provide a complete methodology to analyze finite multivariate mixture models. Our approach is fully nonparametric and it… (more)

Subjects/Keywords: Density Estimation; EM Algorithm; Nonparametric Mixture; Multivariate Mixture

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APA (6th Edition):

Benaglia, T. A. (2008). NONPARAMETRIC ESTIMATION IN MULTIVARIATE FINITE MIXTURE MODELS. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9263

Chicago Manual of Style (16th Edition):

Benaglia, Tatiana A. “NONPARAMETRIC ESTIMATION IN MULTIVARIATE FINITE MIXTURE MODELS.” 2008. Doctoral Dissertation, Penn State University. Accessed August 07, 2020. https://etda.libraries.psu.edu/catalog/9263.

MLA Handbook (7th Edition):

Benaglia, Tatiana A. “NONPARAMETRIC ESTIMATION IN MULTIVARIATE FINITE MIXTURE MODELS.” 2008. Web. 07 Aug 2020.

Vancouver:

Benaglia TA. NONPARAMETRIC ESTIMATION IN MULTIVARIATE FINITE MIXTURE MODELS. [Internet] [Doctoral dissertation]. Penn State University; 2008. [cited 2020 Aug 07]. Available from: https://etda.libraries.psu.edu/catalog/9263.

Council of Science Editors:

Benaglia TA. NONPARAMETRIC ESTIMATION IN MULTIVARIATE FINITE MIXTURE MODELS. [Doctoral Dissertation]. Penn State University; 2008. Available from: https://etda.libraries.psu.edu/catalog/9263


Penn State University

9. Liu, Rong. MULTIPLE IMPUTATION FOR MISSING ITEMS IN MULTI-THEMED QUESTIONNAIRES.

Degree: PhD, Statistics, 2010, Penn State University

 Questionnaires used in survey-based research are often arranged in multiple sections. Each section contains items that are closely interrelated, serving one or more themes. Even… (more)

Subjects/Keywords: factor model; EM algorithm; Markov chain Monte Carlo; incomplete data

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APA (6th Edition):

Liu, R. (2010). MULTIPLE IMPUTATION FOR MISSING ITEMS IN MULTI-THEMED QUESTIONNAIRES. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/10552

Chicago Manual of Style (16th Edition):

Liu, Rong. “MULTIPLE IMPUTATION FOR MISSING ITEMS IN MULTI-THEMED QUESTIONNAIRES.” 2010. Doctoral Dissertation, Penn State University. Accessed August 07, 2020. https://etda.libraries.psu.edu/catalog/10552.

MLA Handbook (7th Edition):

Liu, Rong. “MULTIPLE IMPUTATION FOR MISSING ITEMS IN MULTI-THEMED QUESTIONNAIRES.” 2010. Web. 07 Aug 2020.

Vancouver:

Liu R. MULTIPLE IMPUTATION FOR MISSING ITEMS IN MULTI-THEMED QUESTIONNAIRES. [Internet] [Doctoral dissertation]. Penn State University; 2010. [cited 2020 Aug 07]. Available from: https://etda.libraries.psu.edu/catalog/10552.

Council of Science Editors:

Liu R. MULTIPLE IMPUTATION FOR MISSING ITEMS IN MULTI-THEMED QUESTIONNAIRES. [Doctoral Dissertation]. Penn State University; 2010. Available from: https://etda.libraries.psu.edu/catalog/10552

10. Chen, Weihan. A gradient model for studying genotype-.

Degree: MS, Statistics, 2011, Penn State University

 The genetic architecture of how genes interact with the environemnt to determine complex phenotypes remains eclusive. We know little about the genes that underlie the… (more)

Subjects/Keywords: QTL genotypes; EM algorithm

…selection in covariance structure. Estimation and Tests. A hybrid EM-simplex algorithm was… …environments, and the parameters that model the covariance structure. The EM algorithm provides a… …platform within which the simplex algorithm is embedded to estimate . After all the parameters… 

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APA (6th Edition):

Chen, W. (2011). A gradient model for studying genotype-. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/11889

Chicago Manual of Style (16th Edition):

Chen, Weihan. “A gradient model for studying genotype-.” 2011. Masters Thesis, Penn State University. Accessed August 07, 2020. https://etda.libraries.psu.edu/catalog/11889.

MLA Handbook (7th Edition):

Chen, Weihan. “A gradient model for studying genotype-.” 2011. Web. 07 Aug 2020.

Vancouver:

Chen W. A gradient model for studying genotype-. [Internet] [Masters thesis]. Penn State University; 2011. [cited 2020 Aug 07]. Available from: https://etda.libraries.psu.edu/catalog/11889.

Council of Science Editors:

Chen W. A gradient model for studying genotype-. [Masters Thesis]. Penn State University; 2011. Available from: https://etda.libraries.psu.edu/catalog/11889


University of Alberta

11. Ranjan, Rishik. Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization.

Degree: MS, Department of Chemical and Materials Engineering, 2015, University of Alberta

 Availability of large amounts of industrial process data is allowing researchers to explore new data-based modelling methods. In this thesis, Gaussian process (GP) regression, a… (more)

Subjects/Keywords: SAGD; Optimization; Outliers; Robust identification; Gaussian process regression; EM algorithm

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APA (6th Edition):

Ranjan, R. (2015). Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/b2773z58w

Chicago Manual of Style (16th Edition):

Ranjan, Rishik. “Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization.” 2015. Masters Thesis, University of Alberta. Accessed August 07, 2020. https://era.library.ualberta.ca/files/b2773z58w.

MLA Handbook (7th Edition):

Ranjan, Rishik. “Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization.” 2015. Web. 07 Aug 2020.

Vancouver:

Ranjan R. Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2020 Aug 07]. Available from: https://era.library.ualberta.ca/files/b2773z58w.

Council of Science Editors:

Ranjan R. Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization. [Masters Thesis]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/b2773z58w


University of Oulu

12. Nissilä, M. (Mauri). Iterative receivers for digital communications via variational inference and estimation.

Degree: 2008, University of Oulu

 Abstract In this thesis, iterative detection and estimation algorithms for digital communications systems in the presence of parametric uncertainty are explored and further developed. In… (more)

Subjects/Keywords: Bayesian inference and estimation; EM algorithm; frequency offset estimation; turbo receivers

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APA (6th Edition):

Nissilä, M. (. (2008). Iterative receivers for digital communications via variational inference and estimation. (Doctoral Dissertation). University of Oulu. Retrieved from http://urn.fi/urn:isbn:9789514286865

Chicago Manual of Style (16th Edition):

Nissilä, M (Mauri). “Iterative receivers for digital communications via variational inference and estimation.” 2008. Doctoral Dissertation, University of Oulu. Accessed August 07, 2020. http://urn.fi/urn:isbn:9789514286865.

MLA Handbook (7th Edition):

Nissilä, M (Mauri). “Iterative receivers for digital communications via variational inference and estimation.” 2008. Web. 07 Aug 2020.

Vancouver:

Nissilä M(. Iterative receivers for digital communications via variational inference and estimation. [Internet] [Doctoral dissertation]. University of Oulu; 2008. [cited 2020 Aug 07]. Available from: http://urn.fi/urn:isbn:9789514286865.

Council of Science Editors:

Nissilä M(. Iterative receivers for digital communications via variational inference and estimation. [Doctoral Dissertation]. University of Oulu; 2008. Available from: http://urn.fi/urn:isbn:9789514286865


North Carolina State University

13. Gong, Xiaohua. Mapping Quantitative Trait Loci in Outbred Half-sib Populations.

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

 Quantitative trait loci (QTL) mapping in outbred populations faces some challenges unique to the divergent genetic background and complex pedigree relationships. Motivated by a dairy… (more)

Subjects/Keywords: QTL; half-sib; variance component; mixed model; EM algorithm; haplotyping

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APA (6th Edition):

Gong, X. (2009). Mapping Quantitative Trait Loci in Outbred Half-sib Populations. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/4283

Chicago Manual of Style (16th Edition):

Gong, Xiaohua. “Mapping Quantitative Trait Loci in Outbred Half-sib Populations.” 2009. Doctoral Dissertation, North Carolina State University. Accessed August 07, 2020. http://www.lib.ncsu.edu/resolver/1840.16/4283.

MLA Handbook (7th Edition):

Gong, Xiaohua. “Mapping Quantitative Trait Loci in Outbred Half-sib Populations.” 2009. Web. 07 Aug 2020.

Vancouver:

Gong X. Mapping Quantitative Trait Loci in Outbred Half-sib Populations. [Internet] [Doctoral dissertation]. North Carolina State University; 2009. [cited 2020 Aug 07]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4283.

Council of Science Editors:

Gong X. Mapping Quantitative Trait Loci in Outbred Half-sib Populations. [Doctoral Dissertation]. North Carolina State University; 2009. Available from: http://www.lib.ncsu.edu/resolver/1840.16/4283


NSYSU

14. Lin, Hung-Fu. Joint Detection and Estimation in Cooperative Communication Systems with Correlated Channels Using EM Algorithm.

Degree: Master, Communications Engineering, 2010, NSYSU

 In this thesis, we consider the problem of distributed detection problem in cooperative communication networks when the channel state information (CSI) is unknown. The amplify-and-forward… (more)

Subjects/Keywords: EM Algorithm; joint detection and estimation; Amplify-and-Forward

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APA (6th Edition):

Lin, H. (2010). Joint Detection and Estimation in Cooperative Communication Systems with Correlated Channels Using EM Algorithm. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719110-174552

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):

Lin, Hung-Fu. “Joint Detection and Estimation in Cooperative Communication Systems with Correlated Channels Using EM Algorithm.” 2010. Thesis, NSYSU. Accessed August 07, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719110-174552.

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

MLA Handbook (7th Edition):

Lin, Hung-Fu. “Joint Detection and Estimation in Cooperative Communication Systems with Correlated Channels Using EM Algorithm.” 2010. Web. 07 Aug 2020.

Vancouver:

Lin H. Joint Detection and Estimation in Cooperative Communication Systems with Correlated Channels Using EM Algorithm. [Internet] [Thesis]. NSYSU; 2010. [cited 2020 Aug 07]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719110-174552.

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

Council of Science Editors:

Lin H. Joint Detection and Estimation in Cooperative Communication Systems with Correlated Channels Using EM Algorithm. [Thesis]. NSYSU; 2010. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719110-174552

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


University of Alberta

15. Wu, Ouyang. <em class="hilite">EMem> Algorithm for Electricity Pool Price Prediction and Errors-in-variables Process Identification.

Degree: MS, Department of Chemical and Materials Engineering, 2015, University of Alberta

 In this thesis, under the EM algorithm framework, a multiple model approach is developed towards electricity price prediction, and the identification problem for errors-in-variables (EIV)… (more)

Subjects/Keywords: Pool price prediction; EM algorithm; Multiple model; Errors-in-variables

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APA (6th Edition):

Wu, O. (2015). EM Algorithm for Electricity Pool Price Prediction and Errors-in-variables Process Identification. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/ccf95jb53m

Chicago Manual of Style (16th Edition):

Wu, Ouyang. “EM Algorithm for Electricity Pool Price Prediction and Errors-in-variables Process Identification.” 2015. Masters Thesis, University of Alberta. Accessed August 07, 2020. https://era.library.ualberta.ca/files/ccf95jb53m.

MLA Handbook (7th Edition):

Wu, Ouyang. “EM Algorithm for Electricity Pool Price Prediction and Errors-in-variables Process Identification.” 2015. Web. 07 Aug 2020.

Vancouver:

Wu O. EM Algorithm for Electricity Pool Price Prediction and Errors-in-variables Process Identification. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2020 Aug 07]. Available from: https://era.library.ualberta.ca/files/ccf95jb53m.

Council of Science Editors:

Wu O. EM Algorithm for Electricity Pool Price Prediction and Errors-in-variables Process Identification. [Masters Thesis]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/ccf95jb53m


University of Waikato

16. 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 August 07, 2020. http://hdl.handle.net/10289/5110.

MLA Handbook (7th Edition):

Rohan, Maheswaran. “Using Finite Mixtures to Robustify Statistical Models .” 2011. Web. 07 Aug 2020.

Vancouver:

Rohan M. Using Finite Mixtures to Robustify Statistical Models . [Internet] [Doctoral dissertation]. University of Waikato; 2011. [cited 2020 Aug 07]. 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


Duke University

17. Solomon, Nicole Chanel. Extending Probabilistic Record Linkage .

Degree: 2020, Duke University

  Probabilistic record linkage is the task of combining multiple data sources for statistical analysis by identifying records pertaining to the same individual in different… (more)

Subjects/Keywords: Biostatistics; data-driven; EM algorithm; identifiability; mixture model; record linkage

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APA (6th Edition):

Solomon, N. C. (2020). Extending Probabilistic Record Linkage . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/20891

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):

Solomon, Nicole Chanel. “Extending Probabilistic Record Linkage .” 2020. Thesis, Duke University. Accessed August 07, 2020. http://hdl.handle.net/10161/20891.

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

MLA Handbook (7th Edition):

Solomon, Nicole Chanel. “Extending Probabilistic Record Linkage .” 2020. Web. 07 Aug 2020.

Vancouver:

Solomon NC. Extending Probabilistic Record Linkage . [Internet] [Thesis]. Duke University; 2020. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/10161/20891.

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

Council of Science Editors:

Solomon NC. Extending Probabilistic Record Linkage . [Thesis]. Duke University; 2020. Available from: http://hdl.handle.net/10161/20891

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


Virginia Tech

18. Chen, Shuo. The Application of the Expectation-Maximization Algorithm to the Identification of Biological Models.

Degree: MS, Electrical and Computer Engineering, 2006, Virginia Tech

 With the onset of large-scale gene expression profiling, many researchers have turned their attention toward biological process modeling and system identification. The abundance of data… (more)

Subjects/Keywords: Gene Regulatory Networks; EM Algorithm

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APA (6th Edition):

Chen, S. (2006). The Application of the Expectation-Maximization Algorithm to the Identification of Biological Models. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/36160

Chicago Manual of Style (16th Edition):

Chen, Shuo. “The Application of the Expectation-Maximization Algorithm to the Identification of Biological Models.” 2006. Masters Thesis, Virginia Tech. Accessed August 07, 2020. http://hdl.handle.net/10919/36160.

MLA Handbook (7th Edition):

Chen, Shuo. “The Application of the Expectation-Maximization Algorithm to the Identification of Biological Models.” 2006. Web. 07 Aug 2020.

Vancouver:

Chen S. The Application of the Expectation-Maximization Algorithm to the Identification of Biological Models. [Internet] [Masters thesis]. Virginia Tech; 2006. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/10919/36160.

Council of Science Editors:

Chen S. The Application of the Expectation-Maximization Algorithm to the Identification of Biological Models. [Masters Thesis]. Virginia Tech; 2006. Available from: http://hdl.handle.net/10919/36160


Texas A&M University

19. Balogun, Oluwafemi Opeyemi. New History Matching Methodology for Two Phase Reservoir Using Expectation-Maximization (EM) Algorithm.

Degree: PhD, Petroleum Engineering, 2017, Texas A&M University

 The Expectation-Maximization (EM) Algorithm is a well-known method for estimating maximum likelihood and can be used to find missing numbers in an array. The EM(more)

Subjects/Keywords: History Matching; EM Algorithm; Oil Reservoir; Reservoir Simulation

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APA (6th Edition):

Balogun, O. O. (2017). New History Matching Methodology for Two Phase Reservoir Using Expectation-Maximization (EM) Algorithm. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/173215

Chicago Manual of Style (16th Edition):

Balogun, Oluwafemi Opeyemi. “New History Matching Methodology for Two Phase Reservoir Using Expectation-Maximization (EM) Algorithm.” 2017. Doctoral Dissertation, Texas A&M University. Accessed August 07, 2020. http://hdl.handle.net/1969.1/173215.

MLA Handbook (7th Edition):

Balogun, Oluwafemi Opeyemi. “New History Matching Methodology for Two Phase Reservoir Using Expectation-Maximization (EM) Algorithm.” 2017. Web. 07 Aug 2020.

Vancouver:

Balogun OO. New History Matching Methodology for Two Phase Reservoir Using Expectation-Maximization (EM) Algorithm. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/1969.1/173215.

Council of Science Editors:

Balogun OO. New History Matching Methodology for Two Phase Reservoir Using Expectation-Maximization (EM) Algorithm. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/173215


King Abdullah University of Science and Technology

20. Meng, Rui. Growth Curve Analysis and Change-Points Detection in Extremes.

Degree: 2016, King Abdullah University of Science and Technology

 The thesis consists of two coherent projects. The first project presents the results of evaluating salinity tolerance in barley using growth curve analysis where different… (more)

Subjects/Keywords: functional data; fitting; functional data registration; ANOVA model; algorithm; EM

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APA (6th Edition):

Meng, R. (2016). Growth Curve Analysis and Change-Points Detection in Extremes. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/609833

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):

Meng, Rui. “Growth Curve Analysis and Change-Points Detection in Extremes.” 2016. Thesis, King Abdullah University of Science and Technology. Accessed August 07, 2020. http://hdl.handle.net/10754/609833.

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

MLA Handbook (7th Edition):

Meng, Rui. “Growth Curve Analysis and Change-Points Detection in Extremes.” 2016. Web. 07 Aug 2020.

Vancouver:

Meng R. Growth Curve Analysis and Change-Points Detection in Extremes. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2016. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/10754/609833.

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

Council of Science Editors:

Meng R. Growth Curve Analysis and Change-Points Detection in Extremes. [Thesis]. King Abdullah University of Science and Technology; 2016. Available from: http://hdl.handle.net/10754/609833

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


University of Toledo

21. Chowdhury, Tashnim Jabir Shovon. A distributed cooperative algorithm for localization in wireless sensor networks using Gaussian mixture modeling.

Degree: MS, Electrical Engineering, 2016, University of Toledo

 Wireless sensor networks are defined as spatially distributed autonomous sensors to monitor certain physical or environmental conditions like temperature, pressure, sound, etc. and incorporate the… (more)

Subjects/Keywords: Electrical Engineering; Localization; wireless sensor networks; Gaussian mixture modeling; EM algorithm

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APA (6th Edition):

Chowdhury, T. J. S. (2016). A distributed cooperative algorithm for localization in wireless sensor networks using Gaussian mixture modeling. (Masters Thesis). University of Toledo. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=toledo1481227449382602

Chicago Manual of Style (16th Edition):

Chowdhury, Tashnim Jabir Shovon. “A distributed cooperative algorithm for localization in wireless sensor networks using Gaussian mixture modeling.” 2016. Masters Thesis, University of Toledo. Accessed August 07, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1481227449382602.

MLA Handbook (7th Edition):

Chowdhury, Tashnim Jabir Shovon. “A distributed cooperative algorithm for localization in wireless sensor networks using Gaussian mixture modeling.” 2016. Web. 07 Aug 2020.

Vancouver:

Chowdhury TJS. A distributed cooperative algorithm for localization in wireless sensor networks using Gaussian mixture modeling. [Internet] [Masters thesis]. University of Toledo; 2016. [cited 2020 Aug 07]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1481227449382602.

Council of Science Editors:

Chowdhury TJS. A distributed cooperative algorithm for localization in wireless sensor networks using Gaussian mixture modeling. [Masters Thesis]. University of Toledo; 2016. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1481227449382602

22. Xiang, Sijia. Minimum Hellinger distance estimation in a semiparametric mixture model.

Degree: MS, Department of Statistics, 2012, Kansas State University

 In this report, we introduce the minimum Hellinger distance (MHD) estimation method and review its history. We examine the use of Hellinger distance to obtain… (more)

Subjects/Keywords: Semiparametric mixture models; Minimum Hellinger distance; Semiparametric EM algorithm; Statistics (0463)

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APA (6th Edition):

Xiang, S. (2012). Minimum Hellinger distance estimation in a semiparametric mixture model. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/13762

Chicago Manual of Style (16th Edition):

Xiang, Sijia. “Minimum Hellinger distance estimation in a semiparametric mixture model.” 2012. Masters Thesis, Kansas State University. Accessed August 07, 2020. http://hdl.handle.net/2097/13762.

MLA Handbook (7th Edition):

Xiang, Sijia. “Minimum Hellinger distance estimation in a semiparametric mixture model.” 2012. Web. 07 Aug 2020.

Vancouver:

Xiang S. Minimum Hellinger distance estimation in a semiparametric mixture model. [Internet] [Masters thesis]. Kansas State University; 2012. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2097/13762.

Council of Science Editors:

Xiang S. Minimum Hellinger distance estimation in a semiparametric mixture model. [Masters Thesis]. Kansas State University; 2012. Available from: http://hdl.handle.net/2097/13762


University of Illinois – Chicago

23. Langi, Fima Lanra Fredrik Gerarld. Analysis of Survey Data with Non-Ignorable Missing Covariates.

Degree: 2017, University of Illinois – Chicago

 Missing data are common in survey sampling, which create a spectrum of inferential problems. In this thesis, a method to analyze survey data with potentially… (more)

Subjects/Keywords: missing data; survey sampling; maximum likelihood; EM algorithm

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APA (6th Edition):

Langi, F. L. F. G. (2017). Analysis of Survey Data with Non-Ignorable Missing Covariates. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/22133

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):

Langi, Fima Lanra Fredrik Gerarld. “Analysis of Survey Data with Non-Ignorable Missing Covariates.” 2017. Thesis, University of Illinois – Chicago. Accessed August 07, 2020. http://hdl.handle.net/10027/22133.

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

MLA Handbook (7th Edition):

Langi, Fima Lanra Fredrik Gerarld. “Analysis of Survey Data with Non-Ignorable Missing Covariates.” 2017. Web. 07 Aug 2020.

Vancouver:

Langi FLFG. Analysis of Survey Data with Non-Ignorable Missing Covariates. [Internet] [Thesis]. University of Illinois – Chicago; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/10027/22133.

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

Council of Science Editors:

Langi FLFG. Analysis of Survey Data with Non-Ignorable Missing Covariates. [Thesis]. University of Illinois – Chicago; 2017. Available from: http://hdl.handle.net/10027/22133

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

24. Kilpatrick, Alastair Morris. Novel stochastic and entropy-based Expectation-Maximisation algorithm for transcription factor binding site motif discovery.

Degree: PhD, 2015, University of Edinburgh

 The discovery of transcription factor binding site (TFBS) motifs remains an important and challenging problem in computational biology. This thesis presents MITSU, a novel algorithm(more)

Subjects/Keywords: 572.8; stochastic Expectation- Maximisation; stochastic EM; algorithm; motif discovery

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APA (6th Edition):

Kilpatrick, A. M. (2015). Novel stochastic and entropy-based Expectation-Maximisation algorithm for transcription factor binding site motif discovery. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/10489

Chicago Manual of Style (16th Edition):

Kilpatrick, Alastair Morris. “Novel stochastic and entropy-based Expectation-Maximisation algorithm for transcription factor binding site motif discovery.” 2015. Doctoral Dissertation, University of Edinburgh. Accessed August 07, 2020. http://hdl.handle.net/1842/10489.

MLA Handbook (7th Edition):

Kilpatrick, Alastair Morris. “Novel stochastic and entropy-based Expectation-Maximisation algorithm for transcription factor binding site motif discovery.” 2015. Web. 07 Aug 2020.

Vancouver:

Kilpatrick AM. Novel stochastic and entropy-based Expectation-Maximisation algorithm for transcription factor binding site motif discovery. [Internet] [Doctoral dissertation]. University of Edinburgh; 2015. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/1842/10489.

Council of Science Editors:

Kilpatrick AM. Novel stochastic and entropy-based Expectation-Maximisation algorithm for transcription factor binding site motif discovery. [Doctoral Dissertation]. University of Edinburgh; 2015. Available from: http://hdl.handle.net/1842/10489


University of Sydney

25. Fitzpatrick, Matthew Anthony. Multi-regime models involving Markov chains .

Degree: 2016, University of Sydney

 In this work, we explore the theory and applications of various multi-regime models involving Markov chains. Markov chains are an elegant way to model path-dependent… (more)

Subjects/Keywords: Mixture models; Regime-switching; Change-point; MCMC; EM-Algorithm; Markov Chains

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APA (6th Edition):

Fitzpatrick, M. A. (2016). Multi-regime models involving Markov chains . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/14530

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):

Fitzpatrick, Matthew Anthony. “Multi-regime models involving Markov chains .” 2016. Thesis, University of Sydney. Accessed August 07, 2020. http://hdl.handle.net/2123/14530.

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

MLA Handbook (7th Edition):

Fitzpatrick, Matthew Anthony. “Multi-regime models involving Markov chains .” 2016. Web. 07 Aug 2020.

Vancouver:

Fitzpatrick MA. Multi-regime models involving Markov chains . [Internet] [Thesis]. University of Sydney; 2016. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2123/14530.

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

Council of Science Editors:

Fitzpatrick MA. Multi-regime models involving Markov chains . [Thesis]. University of Sydney; 2016. Available from: http://hdl.handle.net/2123/14530

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


University of Kentucky

26. Zhou, Feng. Contaminated Chi-square Modeling and Its Application in Microarray Data Analysis.

Degree: 2014, University of Kentucky

 Mixture modeling has numerous applications. One particular interest is microarray data analysis. My dissertation research is focused on the Contaminated Chi-Square (CCS) Modeling and its… (more)

Subjects/Keywords: Contaminated Chi-Square Model; EM Algorithm; MLRT; Microarray; Mixture Model; Microarrays

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APA (6th Edition):

Zhou, F. (2014). Contaminated Chi-square Modeling and Its Application in Microarray Data Analysis. (Doctoral Dissertation). University of Kentucky. Retrieved from https://uknowledge.uky.edu/statistics_etds/7

Chicago Manual of Style (16th Edition):

Zhou, Feng. “Contaminated Chi-square Modeling and Its Application in Microarray Data Analysis.” 2014. Doctoral Dissertation, University of Kentucky. Accessed August 07, 2020. https://uknowledge.uky.edu/statistics_etds/7.

MLA Handbook (7th Edition):

Zhou, Feng. “Contaminated Chi-square Modeling and Its Application in Microarray Data Analysis.” 2014. Web. 07 Aug 2020.

Vancouver:

Zhou F. Contaminated Chi-square Modeling and Its Application in Microarray Data Analysis. [Internet] [Doctoral dissertation]. University of Kentucky; 2014. [cited 2020 Aug 07]. Available from: https://uknowledge.uky.edu/statistics_etds/7.

Council of Science Editors:

Zhou F. Contaminated Chi-square Modeling and Its Application in Microarray Data Analysis. [Doctoral Dissertation]. University of Kentucky; 2014. Available from: https://uknowledge.uky.edu/statistics_etds/7


University of Kentucky

27. Wang, Hongyuan. Statistical Inference on Dynamical Systems.

Degree: 2016, University of Kentucky

 The ordinary differential equation (ODE) is one representative and popular tool in modeling dynamical systems, which are widely implemented in physics, biology, economics, chemistry and… (more)

Subjects/Keywords: Dynamical System; ODE; Computational Statistics; EM Algorithm; Statistical Models

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APA (6th Edition):

Wang, H. (2016). Statistical Inference on Dynamical Systems. (Doctoral Dissertation). University of Kentucky. Retrieved from https://uknowledge.uky.edu/statistics_etds/22

Chicago Manual of Style (16th Edition):

Wang, Hongyuan. “Statistical Inference on Dynamical Systems.” 2016. Doctoral Dissertation, University of Kentucky. Accessed August 07, 2020. https://uknowledge.uky.edu/statistics_etds/22.

MLA Handbook (7th Edition):

Wang, Hongyuan. “Statistical Inference on Dynamical Systems.” 2016. Web. 07 Aug 2020.

Vancouver:

Wang H. Statistical Inference on Dynamical Systems. [Internet] [Doctoral dissertation]. University of Kentucky; 2016. [cited 2020 Aug 07]. Available from: https://uknowledge.uky.edu/statistics_etds/22.

Council of Science Editors:

Wang H. Statistical Inference on Dynamical Systems. [Doctoral Dissertation]. University of Kentucky; 2016. Available from: https://uknowledge.uky.edu/statistics_etds/22


University of Adelaide

28. Diassinas, Christopher Luke. [EMBARGOED] Application of Expectation Maximisation Algorithm on Mixed Distributions.

Degree: 2019, University of Adelaide

 Mixed distributions are a statistical tool used for modelling a range of phenomena in fields as diverse as marketing, genetics, medicine, artificial intelligence, and finance.… (more)

Subjects/Keywords: EM algorithm; mixed distributions; statistics; goodness-of-fit; econophysics; Monte Carlo

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APA (6th Edition):

Diassinas, C. L. (2019). [EMBARGOED] Application of Expectation Maximisation Algorithm on Mixed Distributions. (Thesis). University of Adelaide. Retrieved from http://hdl.handle.net/2440/119934

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):

Diassinas, Christopher Luke. “[EMBARGOED] Application of Expectation Maximisation Algorithm on Mixed Distributions.” 2019. Thesis, University of Adelaide. Accessed August 07, 2020. http://hdl.handle.net/2440/119934.

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

MLA Handbook (7th Edition):

Diassinas, Christopher Luke. “[EMBARGOED] Application of Expectation Maximisation Algorithm on Mixed Distributions.” 2019. Web. 07 Aug 2020.

Vancouver:

Diassinas CL. [EMBARGOED] Application of Expectation Maximisation Algorithm on Mixed Distributions. [Internet] [Thesis]. University of Adelaide; 2019. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/2440/119934.

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

Council of Science Editors:

Diassinas CL. [EMBARGOED] Application of Expectation Maximisation Algorithm on Mixed Distributions. [Thesis]. University of Adelaide; 2019. Available from: http://hdl.handle.net/2440/119934

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


University of Victoria

29. Li, Hang. Parameter estimation of queueing system using mixture model and the EM algorithm.

Degree: Department of Computer Science, 2016, University of Victoria

 Parameter estimation is a long-lasting topic in queueing systems and has attracted considerable attention from both academia and industry. In this thesis, we design a… (more)

Subjects/Keywords: EM algorithm; Queueing Theory; Mixture Model; Tandem Queueing System

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APA (6th Edition):

Li, H. (2016). Parameter estimation of queueing system using mixture model and the EM algorithm. (Masters Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/7647

Chicago Manual of Style (16th Edition):

Li, Hang. “Parameter estimation of queueing system using mixture model and the EM algorithm.” 2016. Masters Thesis, University of Victoria. Accessed August 07, 2020. http://hdl.handle.net/1828/7647.

MLA Handbook (7th Edition):

Li, Hang. “Parameter estimation of queueing system using mixture model and the EM algorithm.” 2016. Web. 07 Aug 2020.

Vancouver:

Li H. Parameter estimation of queueing system using mixture model and the EM algorithm. [Internet] [Masters thesis]. University of Victoria; 2016. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/1828/7647.

Council of Science Editors:

Li H. Parameter estimation of queueing system using mixture model and the EM algorithm. [Masters Thesis]. University of Victoria; 2016. Available from: http://hdl.handle.net/1828/7647


University of KwaZulu-Natal

30. Ndlela, Thamsanqa Innocent. Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data.

Degree: 2017, University of KwaZulu-Natal

 Missing data is a very serious issue that negatively affect inferences and findings of researchers in data science and statistics. The ignorance of missing data… (more)

Subjects/Keywords: Cancer.; EM Algorithm.; Data augmentation.; Bayesian approach.; Missing data.

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APA (6th Edition):

Ndlela, T. I. (2017). Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data. (Thesis). University of KwaZulu-Natal. Retrieved from http://hdl.handle.net/10413/15641

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):

Ndlela, Thamsanqa Innocent. “Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data.” 2017. Thesis, University of KwaZulu-Natal. Accessed August 07, 2020. http://hdl.handle.net/10413/15641.

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

MLA Handbook (7th Edition):

Ndlela, Thamsanqa Innocent. “Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data.” 2017. Web. 07 Aug 2020.

Vancouver:

Ndlela TI. Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data. [Internet] [Thesis]. University of KwaZulu-Natal; 2017. [cited 2020 Aug 07]. Available from: http://hdl.handle.net/10413/15641.

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

Council of Science Editors:

Ndlela TI. Bayesian data augmentation using MCMC: application to missing values imputation on cancer medication data. [Thesis]. University of KwaZulu-Natal; 2017. Available from: http://hdl.handle.net/10413/15641

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

[1] [2] [3] [4] [5] [6] [7] [8] [9]

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