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- 2011 – 2015 (112)
- 2006 – 2010 (65)
- 2001 – 2005 (24)

Universities

- University of São Paulo (17)
- Kansas State University (11)
- Penn State University (10)

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- Statistics (25)
- Department of Statistics (11)

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- PhD (65)
- MS (27)
- Docteur es (24)

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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

URL: etd-042513-091152 ; https://digitalcommons.wpi.edu/etd-theses/290

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

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

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

URL: https://etda.libraries.psu.edu/catalog/21780

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

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

URL: https://era.library.ualberta.ca/files/k643b130g

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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.

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

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

URL: https://era.library.ualberta.ca/files/7p88ch465

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

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

URL: http://hdl.handle.net/2142/98245

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

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

URL: http://tede.unioeste.br/tede//tde_busca/arquivo.php?codArquivo=802

►

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

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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: https://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. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/22368

Chicago Manual of Style (16^{th} 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 (7^{th} 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

URL: https://etda.libraries.psu.edu/catalog/9263

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

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

URL: https://etda.libraries.psu.edu/catalog/10552

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

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

URL: https://etda.libraries.psu.edu/catalog/11889

► 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…

Record Details Similar Records

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

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

URL: https://era.library.ualberta.ca/files/b2773z58w

► 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

Record Details Similar Records

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

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

URL: http://urn.fi/urn:isbn:9789514286865

► 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

Record Details Similar Records

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

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

URL: http://www.lib.ncsu.edu/resolver/1840.16/4283

► 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

Record Details Similar Records

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

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

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0719110-174552

► 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

Record Details Similar Records

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APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

Not specified: Masters Thesis or Doctoral Dissertation

University of Alberta

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

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

URL: https://era.library.ualberta.ca/files/ccf95jb53m

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

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

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

MLA Handbook (7^{th} 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

URL: http://hdl.handle.net/10161/20891

► 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 (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

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

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

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/10919/36160

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1969.1/173215

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/10754/609833

► 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 (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://rave.ohiolink.edu/etdc/view?acc_num=toledo1481227449382602

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/2097/13762

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/10027/22133

► 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 (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/1842/10489

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/2123/14530

► 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 (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: https://uknowledge.uky.edu/statistics_etds/7

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: https://uknowledge.uky.edu/statistics_etds/22

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/2440/119934

► 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 (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/1828/7647

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/10413/15641

► 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 (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

Not specified: Masters Thesis or Doctoral Dissertation