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- 2005 – 2009 (25)

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Penn State University

1.
Feng, Yijia.
* Robust* Nonparametric Function Estimation with Serially
Correlated Data.

Degree: PhD, Statistics, 2010, Penn State University

URL: https://etda.libraries.psu.edu/catalog/11391

► Nonparametric function estimation via local polynomial *regression* has been widely studied in the literature, especially in the past two decades. In practice, we confront two…
(more)

Subjects/Keywords: autoregressive process; local linear regression; robust regression

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

APA (6^{th} Edition):

Feng, Y. (2010). Robust Nonparametric Function Estimation with Serially Correlated Data. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/11391

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

Feng, Yijia. “Robust Nonparametric Function Estimation with Serially Correlated Data.” 2010. Doctoral Dissertation, Penn State University. Accessed July 19, 2019. https://etda.libraries.psu.edu/catalog/11391.

MLA Handbook (7^{th} Edition):

Feng, Yijia. “Robust Nonparametric Function Estimation with Serially Correlated Data.” 2010. Web. 19 Jul 2019.

Vancouver:

Feng Y. Robust Nonparametric Function Estimation with Serially Correlated Data. [Internet] [Doctoral dissertation]. Penn State University; 2010. [cited 2019 Jul 19]. Available from: https://etda.libraries.psu.edu/catalog/11391.

Council of Science Editors:

Feng Y. Robust Nonparametric Function Estimation with Serially Correlated Data. [Doctoral Dissertation]. Penn State University; 2010. Available from: https://etda.libraries.psu.edu/catalog/11391

2.
Bai, Xue.
* Robust* linear

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

URL: http://hdl.handle.net/2097/14977

► In practice, when applying a statistical method it often occurs that some observations deviate from the usual model assumptions. Least-squares (LS) estimators are very sensitive…
(more)

Subjects/Keywords: Linear regression model; Robust regression; Statistics (0463)

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APA (6^{th} Edition):

Bai, X. (2012). Robust linear regression. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/14977

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

Bai, Xue. “Robust linear regression.” 2012. Masters Thesis, Kansas State University. Accessed July 19, 2019. http://hdl.handle.net/2097/14977.

MLA Handbook (7^{th} Edition):

Bai, Xue. “Robust linear regression.” 2012. Web. 19 Jul 2019.

Vancouver:

Bai X. Robust linear regression. [Internet] [Masters thesis]. Kansas State University; 2012. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2097/14977.

Council of Science Editors:

Bai X. Robust linear regression. [Masters Thesis]. Kansas State University; 2012. Available from: http://hdl.handle.net/2097/14977

3.
Nunkesser, Robin.
Algorithms for *regression* and
classification.

Degree: 2009, Technische Universität Dortmund

URL: http://hdl.handle.net/2003/26047

► *Regression* and classification are statistical techniques that may be used to extract rules and patterns out of data sets. Analyzing the involved algorithms comprises interdisciplinary…
(more)

Subjects/Keywords: Association studies; Computational statistics; Robust regression; 004

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APA (6^{th} Edition):

Nunkesser, R. (2009). Algorithms for regression and classification. (Thesis). Technische Universität Dortmund. Retrieved from http://hdl.handle.net/2003/26047

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):

Nunkesser, Robin. “Algorithms for regression and classification.” 2009. Thesis, Technische Universität Dortmund. Accessed July 19, 2019. http://hdl.handle.net/2003/26047.

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

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Nunkesser, Robin. “Algorithms for regression and classification.” 2009. Web. 19 Jul 2019.

Vancouver:

Nunkesser R. Algorithms for regression and classification. [Internet] [Thesis]. Technische Universität Dortmund; 2009. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2003/26047.

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

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nunkesser R. Algorithms for regression and classification. [Thesis]. Technische Universität Dortmund; 2009. Available from: http://hdl.handle.net/2003/26047

Not specified: Masters Thesis or Doctoral Dissertation

4.
Bai, Xiuqin.
* Robust*
mixtures of regressions models.

Degree: MS, Department of Statistics, 2010, Kansas State University

URL: http://hdl.handle.net/2097/4613

► In the fitting of mixtures of linear *regression* models, the normal assumption has been traditionally used for the error term and then the *regression* parameters…
(more)

Subjects/Keywords: Robust Mixtures; Regression Models; Statistics (0463)

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APA (6^{th} Edition):

Bai, X. (2010). Robust mixtures of regressions models. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/4613

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

Bai, Xiuqin. “Robust mixtures of regressions models.” 2010. Masters Thesis, Kansas State University. Accessed July 19, 2019. http://hdl.handle.net/2097/4613.

MLA Handbook (7^{th} Edition):

Bai, Xiuqin. “Robust mixtures of regressions models.” 2010. Web. 19 Jul 2019.

Vancouver:

Bai X. Robust mixtures of regressions models. [Internet] [Masters thesis]. Kansas State University; 2010. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2097/4613.

Council of Science Editors:

Bai X. Robust mixtures of regressions models. [Masters Thesis]. Kansas State University; 2010. Available from: http://hdl.handle.net/2097/4613

Kansas State University

5.
McCants, Michael.
Efficacy of
*robust* *regression* applied to fractional factorial treatment
structures.

Degree: MS, Department of Statistics, 2011, Kansas State University

URL: http://hdl.handle.net/2097/9260

► Completely random and randomized block designs involving n factors at each of two levels are used to screen for the effects of a large number…
(more)

Subjects/Keywords: Robust regression; Fractional factorial; Statistics (0463)

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APA (6^{th} Edition):

McCants, M. (2011). Efficacy of robust regression applied to fractional factorial treatment structures. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/9260

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

McCants, Michael. “Efficacy of robust regression applied to fractional factorial treatment structures.” 2011. Masters Thesis, Kansas State University. Accessed July 19, 2019. http://hdl.handle.net/2097/9260.

MLA Handbook (7^{th} Edition):

McCants, Michael. “Efficacy of robust regression applied to fractional factorial treatment structures.” 2011. Web. 19 Jul 2019.

Vancouver:

McCants M. Efficacy of robust regression applied to fractional factorial treatment structures. [Internet] [Masters thesis]. Kansas State University; 2011. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2097/9260.

Council of Science Editors:

McCants M. Efficacy of robust regression applied to fractional factorial treatment structures. [Masters Thesis]. Kansas State University; 2011. Available from: http://hdl.handle.net/2097/9260

Rochester Institute of Technology

6.
Kumar, Pranay.
Experimental Design and *Robust* * Regression*.

Degree: MS, Industrial and Systems Engineering, 2017, Rochester Institute of Technology

URL: https://scholarworks.rit.edu/theses/9666

► Design of Experiments (DOE) is a very powerful statistical methodology, especially when used with linear *regression* analysis. The use of ordinary least squares (OLS)…
(more)

Subjects/Keywords: Design of experiments; Experimental design; Robust regression

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APA (6^{th} Edition):

Kumar, P. (2017). Experimental Design and Robust Regression. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9666

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

Kumar, Pranay. “Experimental Design and Robust Regression.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed July 19, 2019. https://scholarworks.rit.edu/theses/9666.

MLA Handbook (7^{th} Edition):

Kumar, Pranay. “Experimental Design and Robust Regression.” 2017. Web. 19 Jul 2019.

Vancouver:

Kumar P. Experimental Design and Robust Regression. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2019 Jul 19]. Available from: https://scholarworks.rit.edu/theses/9666.

Council of Science Editors:

Kumar P. Experimental Design and Robust Regression. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9666

University of North Texas

7.
Anderson, Cynthia, 1962-.
A Comparison of Five *Robust* *Regression* Methods with Ordinary Least Squares: Relative Efficiency, Bias and Test of the Null Hypothesis.

Degree: 2001, University of North Texas

URL: https://digital.library.unt.edu/ark:/67531/metadc5808/

► A Monte Carlo simulation was used to generate data for a comparison of five *robust* *regression* estimation methods with ordinary least squares (OLS) under 36…
(more)

Subjects/Keywords: Regression analysis.; Robust statistics.; robust regression; outliers; robust statistics

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APA (6^{th} Edition):

Anderson, Cynthia, 1. (2001). A Comparison of Five Robust Regression Methods with Ordinary Least Squares: Relative Efficiency, Bias and Test of the Null Hypothesis. (Thesis). University of North Texas. Retrieved from https://digital.library.unt.edu/ark:/67531/metadc5808/

Not specified: Masters Thesis or Doctoral Dissertation

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

Anderson, Cynthia, 1962-. “A Comparison of Five Robust Regression Methods with Ordinary Least Squares: Relative Efficiency, Bias and Test of the Null Hypothesis.” 2001. Thesis, University of North Texas. Accessed July 19, 2019. https://digital.library.unt.edu/ark:/67531/metadc5808/.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Anderson, Cynthia, 1962-. “A Comparison of Five Robust Regression Methods with Ordinary Least Squares: Relative Efficiency, Bias and Test of the Null Hypothesis.” 2001. Web. 19 Jul 2019.

Vancouver:

Anderson, Cynthia 1. A Comparison of Five Robust Regression Methods with Ordinary Least Squares: Relative Efficiency, Bias and Test of the Null Hypothesis. [Internet] [Thesis]. University of North Texas; 2001. [cited 2019 Jul 19]. Available from: https://digital.library.unt.edu/ark:/67531/metadc5808/.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Anderson, Cynthia 1. A Comparison of Five Robust Regression Methods with Ordinary Least Squares: Relative Efficiency, Bias and Test of the Null Hypothesis. [Thesis]. University of North Texas; 2001. Available from: https://digital.library.unt.edu/ark:/67531/metadc5808/

Not specified: Masters Thesis or Doctoral Dissertation

University of California – San Diego

8.
Liu, Jing.
* Robust* PCA and

Degree: Electrical and Computer Engineering, 2019, University of California – San Diego

URL: http://www.escholarship.org/uc/item/44r1s37c

► Robustness to outliers is of paramount importance in data analytics. However, many data analysis tools are not *robust* to outliers due to their criterion of…
(more)

Subjects/Keywords: Electrical engineering; L0 Regularization; Robust Linear Regression; Robust PCA; Sparse Bayesian Learning

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APA (6^{th} Edition):

Liu, J. (2019). Robust PCA and Robust Linear Regression via Sparsity Regularization. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/44r1s37c

Not specified: Masters Thesis or Doctoral Dissertation

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

Liu, Jing. “Robust PCA and Robust Linear Regression via Sparsity Regularization.” 2019. Thesis, University of California – San Diego. Accessed July 19, 2019. http://www.escholarship.org/uc/item/44r1s37c.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Liu, Jing. “Robust PCA and Robust Linear Regression via Sparsity Regularization.” 2019. Web. 19 Jul 2019.

Vancouver:

Liu J. Robust PCA and Robust Linear Regression via Sparsity Regularization. [Internet] [Thesis]. University of California – San Diego; 2019. [cited 2019 Jul 19]. Available from: http://www.escholarship.org/uc/item/44r1s37c.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Liu J. Robust PCA and Robust Linear Regression via Sparsity Regularization. [Thesis]. University of California – San Diego; 2019. Available from: http://www.escholarship.org/uc/item/44r1s37c

Not specified: Masters Thesis or Doctoral Dissertation

9. Elcio do Nascimento Chagas. Eficiência de estimadores robustos a observações discrepantes em modelo de regressão multivariada com aplicação na análise sensorial do café.

Degree: 2011, UNIVERSIDADE FEDERAL DE LAVRAS

URL: http://bdtd.ufla.br//tde_busca/arquivo.php?codArquivo=3659

►

Dada a sensibilidade do método de mínimos quadrados à presença de observações discrepantes, é sabido que as estimativas de mínimos quadrados são afetadas pela presença… (more)

Subjects/Keywords: análise de regressão; regressão robusta; distância de Mahalanobis; distância robusta; ESTATISTICA; regression analysis; robust regression; mahalanobis distance; robust distance

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

APA (6^{th} Edition):

Chagas, E. d. N. (2011). Eficiência de estimadores robustos a observações discrepantes em modelo de regressão multivariada com aplicação na análise sensorial do café. (Thesis). UNIVERSIDADE FEDERAL DE LAVRAS. Retrieved from http://bdtd.ufla.br//tde_busca/arquivo.php?codArquivo=3659

Not specified: Masters Thesis or Doctoral Dissertation

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

Chagas, Elcio do Nascimento. “Eficiência de estimadores robustos a observações discrepantes em modelo de regressão multivariada com aplicação na análise sensorial do café.” 2011. Thesis, UNIVERSIDADE FEDERAL DE LAVRAS. Accessed July 19, 2019. http://bdtd.ufla.br//tde_busca/arquivo.php?codArquivo=3659.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Chagas, Elcio do Nascimento. “Eficiência de estimadores robustos a observações discrepantes em modelo de regressão multivariada com aplicação na análise sensorial do café.” 2011. Web. 19 Jul 2019.

Vancouver:

Chagas EdN. Eficiência de estimadores robustos a observações discrepantes em modelo de regressão multivariada com aplicação na análise sensorial do café. [Internet] [Thesis]. UNIVERSIDADE FEDERAL DE LAVRAS; 2011. [cited 2019 Jul 19]. Available from: http://bdtd.ufla.br//tde_busca/arquivo.php?codArquivo=3659.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Chagas EdN. Eficiência de estimadores robustos a observações discrepantes em modelo de regressão multivariada com aplicação na análise sensorial do café. [Thesis]. UNIVERSIDADE FEDERAL DE LAVRAS; 2011. Available from: http://bdtd.ufla.br//tde_busca/arquivo.php?codArquivo=3659

Not specified: Masters Thesis or Doctoral Dissertation

10.
Wei, Yan.
* Robust*
mixture

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

URL: http://hdl.handle.net/2097/14110

► In this report, we propose a *robust* mixture of *regression* based on t-distribution by extending the mixture of t-distributions proposed by Peel and McLachlan (2000)…
(more)

Subjects/Keywords: EM algorithm; Mixture regression models; Outliers; Robust regression; T-distribution; Statistics (0463)

Record Details Similar Records

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

APA (6^{th} Edition):

Wei, Y. (2012). Robust mixture regression models using t-distribution. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/14110

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

Wei, Yan. “Robust mixture regression models using t-distribution.” 2012. Masters Thesis, Kansas State University. Accessed July 19, 2019. http://hdl.handle.net/2097/14110.

MLA Handbook (7^{th} Edition):

Wei, Yan. “Robust mixture regression models using t-distribution.” 2012. Web. 19 Jul 2019.

Vancouver:

Wei Y. Robust mixture regression models using t-distribution. [Internet] [Masters thesis]. Kansas State University; 2012. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2097/14110.

Council of Science Editors:

Wei Y. Robust mixture regression models using t-distribution. [Masters Thesis]. Kansas State University; 2012. Available from: http://hdl.handle.net/2097/14110

North-West University

11.
Van der Westhuizen, Magdelena Marianna.
* Robust* techniques for

Degree: 2011, North-West University

URL: http://hdl.handle.net/10394/6689

► Good quality management decisions often rely on the evaluation and interpretation of data. One of the most popular ways to investigate possible relationships in a…
(more)

Subjects/Keywords: Robust regression; Outlier detection; Piecewise linear regression; Linear programming; Smoothing techniques; Optimization

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

APA (6^{th} Edition):

Van der Westhuizen, M. M. (2011). Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen . (Thesis). North-West University. Retrieved from http://hdl.handle.net/10394/6689

Not specified: Masters Thesis or Doctoral Dissertation

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

Van der Westhuizen, Magdelena Marianna. “Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen .” 2011. Thesis, North-West University. Accessed July 19, 2019. http://hdl.handle.net/10394/6689.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Van der Westhuizen, Magdelena Marianna. “Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen .” 2011. Web. 19 Jul 2019.

Vancouver:

Van der Westhuizen MM. Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen . [Internet] [Thesis]. North-West University; 2011. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10394/6689.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Van der Westhuizen MM. Robust techniques for regression models with minimal assumptions / M.M. van der Westhuizen . [Thesis]. North-West University; 2011. Available from: http://hdl.handle.net/10394/6689

Not specified: Masters Thesis or Doctoral Dissertation

12. Kovac, Arne. Wavelet thresholding for unequally time-spaced data.

Degree: 1999, University of Bristol

URL: http://research-information.bristol.ac.uk/en/theses/wavelet-thresholding-for-unequally-timespaced-data(2088715a-7792-4032-bb76-83e3b0389b94).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266951

Subjects/Keywords: 519.5; Adaptive estimation; Robust regression

Record Details Similar Records

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

APA (6^{th} Edition):

Kovac, A. (1999). Wavelet thresholding for unequally time-spaced data. (Doctoral Dissertation). University of Bristol. Retrieved from http://research-information.bristol.ac.uk/en/theses/wavelet-thresholding-for-unequally-timespaced-data(2088715a-7792-4032-bb76-83e3b0389b94).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266951

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

Kovac, Arne. “Wavelet thresholding for unequally time-spaced data.” 1999. Doctoral Dissertation, University of Bristol. Accessed July 19, 2019. http://research-information.bristol.ac.uk/en/theses/wavelet-thresholding-for-unequally-timespaced-data(2088715a-7792-4032-bb76-83e3b0389b94).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266951.

MLA Handbook (7^{th} Edition):

Kovac, Arne. “Wavelet thresholding for unequally time-spaced data.” 1999. Web. 19 Jul 2019.

Vancouver:

Kovac A. Wavelet thresholding for unequally time-spaced data. [Internet] [Doctoral dissertation]. University of Bristol; 1999. [cited 2019 Jul 19]. Available from: http://research-information.bristol.ac.uk/en/theses/wavelet-thresholding-for-unequally-timespaced-data(2088715a-7792-4032-bb76-83e3b0389b94).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266951.

Council of Science Editors:

Kovac A. Wavelet thresholding for unequally time-spaced data. [Doctoral Dissertation]. University of Bristol; 1999. Available from: http://research-information.bristol.ac.uk/en/theses/wavelet-thresholding-for-unequally-timespaced-data(2088715a-7792-4032-bb76-83e3b0389b94).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266951

University of Alberta

13.
Tu, Wei.
* Robust* Adaptively Weighted Estimators for

Degree: MS, Department of Mathematical and Statistical Sciences, 2015, University of Alberta

URL: https://era.library.ualberta.ca/files/zw12z800m

► This thesis introduces a new class of *robust* estimators for *regression* mod- els. Specifically, a class of weighted least square estimators under linear re- gression…
(more)

Subjects/Keywords: weighted estimators; robust statistics; regression model; adaptive estimators

Record Details Similar Records

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

APA (6^{th} Edition):

Tu, W. (2015). Robust Adaptively Weighted Estimators for Regression Models. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/zw12z800m

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

Tu, Wei. “Robust Adaptively Weighted Estimators for Regression Models.” 2015. Masters Thesis, University of Alberta. Accessed July 19, 2019. https://era.library.ualberta.ca/files/zw12z800m.

MLA Handbook (7^{th} Edition):

Tu, Wei. “Robust Adaptively Weighted Estimators for Regression Models.” 2015. Web. 19 Jul 2019.

Vancouver:

Tu W. Robust Adaptively Weighted Estimators for Regression Models. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2019 Jul 19]. Available from: https://era.library.ualberta.ca/files/zw12z800m.

Council of Science Editors:

Tu W. Robust Adaptively Weighted Estimators for Regression Models. [Masters Thesis]. University of Alberta; 2015. Available from: https://era.library.ualberta.ca/files/zw12z800m

University of Alberta

14.
Ranjan, Rishik.
* Robust* Gaussian Process

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 July 19, 2019. 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. 19 Jul 2019.

Vancouver:

Ranjan R. Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization. [Internet] [Masters thesis]. University of Alberta; 2015. [cited 2019 Jul 19]. 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

15. Schettlinger, Karen. Signal and variability extraction for online monitoring in intensive care.

Degree: 2009, Technische Universität Dortmund

URL: http://hdl.handle.net/2003/26044

► This thesis proposes new methods for real-time signal and variability extraction, presents derivations of their robustness properties and discusses their value for practical applications to…
(more)

Subjects/Keywords: Filter; Regression; Robuste Statistik; Robust statistics; Time series; Zeitreihe; 310

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

APA (6^{th} Edition):

Schettlinger, K. (2009). Signal and variability extraction for online monitoring in intensive care. (Thesis). Technische Universität Dortmund. Retrieved from http://hdl.handle.net/2003/26044

Not specified: Masters Thesis or Doctoral Dissertation

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

Schettlinger, Karen. “Signal and variability extraction for online monitoring in intensive care.” 2009. Thesis, Technische Universität Dortmund. Accessed July 19, 2019. http://hdl.handle.net/2003/26044.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Schettlinger, Karen. “Signal and variability extraction for online monitoring in intensive care.” 2009. Web. 19 Jul 2019.

Vancouver:

Schettlinger K. Signal and variability extraction for online monitoring in intensive care. [Internet] [Thesis]. Technische Universität Dortmund; 2009. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/2003/26044.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Schettlinger K. Signal and variability extraction for online monitoring in intensive care. [Thesis]. Technische Universität Dortmund; 2009. Available from: http://hdl.handle.net/2003/26044

Not specified: Masters Thesis or Doctoral Dissertation

NSYSU

16. Wu, Tzung-Han. Study on Ramsay Fuzzy Neural Networks.

Degree: Master, Electrical Engineering, 2008, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0623108-234132

► In this thesis, M-estimators with Ramsayâs function used in *robust* *regression* theory for linear parametric *regression* problems will be generalized to nonparametric Ramsay fuzzy neural…
(more)

Subjects/Keywords: M-estimators; Fuzzy Neural Networks; robust regression; Ramsay

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APA (6^{th} Edition):

Wu, T. (2008). Study on Ramsay Fuzzy Neural Networks. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0623108-234132

Not specified: Masters Thesis or Doctoral Dissertation

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

Wu, Tzung-Han. “Study on Ramsay Fuzzy Neural Networks.” 2008. Thesis, NSYSU. Accessed July 19, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0623108-234132.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Wu, Tzung-Han. “Study on Ramsay Fuzzy Neural Networks.” 2008. Web. 19 Jul 2019.

Vancouver:

Wu T. Study on Ramsay Fuzzy Neural Networks. [Internet] [Thesis]. NSYSU; 2008. [cited 2019 Jul 19]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0623108-234132.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Wu T. Study on Ramsay Fuzzy Neural Networks. [Thesis]. NSYSU; 2008. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0623108-234132

Not specified: Masters Thesis or Doctoral Dissertation

Penn State University

17. Yao, Weixin. On using mixtures and modes of mixtures in data analysis.

Degree: PhD, Statistics, 2007, Penn State University

URL: https://etda.libraries.psu.edu/catalog/7812

My disertation consists two part. In the first part,
we provide a new adaptive robust nonparametric regression. In the
second part, we provide a new method to solve the label switching
for mixture models.

Subjects/Keywords: robust regression; label switching; mixtures

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

APA (6^{th} Edition):

Yao, W. (2007). On using mixtures and modes of mixtures in data analysis. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/7812

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

Yao, Weixin. “On using mixtures and modes of mixtures in data analysis.” 2007. Doctoral Dissertation, Penn State University. Accessed July 19, 2019. https://etda.libraries.psu.edu/catalog/7812.

MLA Handbook (7^{th} Edition):

Yao, Weixin. “On using mixtures and modes of mixtures in data analysis.” 2007. Web. 19 Jul 2019.

Vancouver:

Yao W. On using mixtures and modes of mixtures in data analysis. [Internet] [Doctoral dissertation]. Penn State University; 2007. [cited 2019 Jul 19]. Available from: https://etda.libraries.psu.edu/catalog/7812.

Council of Science Editors:

Yao W. On using mixtures and modes of mixtures in data analysis. [Doctoral Dissertation]. Penn State University; 2007. Available from: https://etda.libraries.psu.edu/catalog/7812

Penn State University

18.
Kai, Bo.
* Robust* Nonparametric and Semiparametric Modeling.

Degree: PhD, Statistics, 2009, Penn State University

URL: https://etda.libraries.psu.edu/catalog/9968

► In this dissertation, several new statistical procedures in nonparametric and semiparametric models are proposed. The concerns of the research are efficiency, robustness and sparsity. In…
(more)

Subjects/Keywords: Nonparametric Smoothing; Semiparametric Modeling; Robust Statistics; Quantile Regression

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APA (6^{th} Edition):

Kai, B. (2009). Robust Nonparametric and Semiparametric Modeling. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9968

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

Kai, Bo. “Robust Nonparametric and Semiparametric Modeling.” 2009. Doctoral Dissertation, Penn State University. Accessed July 19, 2019. https://etda.libraries.psu.edu/catalog/9968.

MLA Handbook (7^{th} Edition):

Kai, Bo. “Robust Nonparametric and Semiparametric Modeling.” 2009. Web. 19 Jul 2019.

Vancouver:

Kai B. Robust Nonparametric and Semiparametric Modeling. [Internet] [Doctoral dissertation]. Penn State University; 2009. [cited 2019 Jul 19]. Available from: https://etda.libraries.psu.edu/catalog/9968.

Council of Science Editors:

Kai B. Robust Nonparametric and Semiparametric Modeling. [Doctoral Dissertation]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9968

Penn State University

19.
Kai, Bo.
Variable Selection in *Robust* Linear Models.

Degree: MS, Statistics, 2008, Penn State University

URL: https://etda.libraries.psu.edu/catalog/8276

► Variable selection plays very important roles in statistical learning. Traditional stepwise subset selection methods are widely used in practice, but they are difficult to implement…
(more)

Subjects/Keywords: robust regression; linear models; variable selection; SS penalty; oracle property

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APA (6^{th} Edition):

Kai, B. (2008). Variable Selection in Robust Linear Models. (Masters Thesis). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/8276

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

Kai, Bo. “Variable Selection in Robust Linear Models.” 2008. Masters Thesis, Penn State University. Accessed July 19, 2019. https://etda.libraries.psu.edu/catalog/8276.

MLA Handbook (7^{th} Edition):

Kai, Bo. “Variable Selection in Robust Linear Models.” 2008. Web. 19 Jul 2019.

Vancouver:

Kai B. Variable Selection in Robust Linear Models. [Internet] [Masters thesis]. Penn State University; 2008. [cited 2019 Jul 19]. Available from: https://etda.libraries.psu.edu/catalog/8276.

Council of Science Editors:

Kai B. Variable Selection in Robust Linear Models. [Masters Thesis]. Penn State University; 2008. Available from: https://etda.libraries.psu.edu/catalog/8276

McGill University

20.
You, Jiazhong, 1968-.
* Robust* estimation and testing : finite-sample properties and econometric applications.

Degree: PhD, Department of Economics., 2000, McGill University

URL: http://digitool.library.mcgill.ca/thesisfile36739.pdf

► High breakdown point, bounded influence and high efficiency at the Gaussian model are desired properties of *robust* *regression* estimators. Robustness of validity, robustness of efficiency…
(more)

Subjects/Keywords: Regression analysis.; Robust statistics.; Econometrics.

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APA (6^{th} Edition):

You, Jiazhong, 1. (2000). Robust estimation and testing : finite-sample properties and econometric applications. (Doctoral Dissertation). McGill University. Retrieved from http://digitool.library.mcgill.ca/thesisfile36739.pdf

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

You, Jiazhong, 1968-. “Robust estimation and testing : finite-sample properties and econometric applications.” 2000. Doctoral Dissertation, McGill University. Accessed July 19, 2019. http://digitool.library.mcgill.ca/thesisfile36739.pdf.

MLA Handbook (7^{th} Edition):

You, Jiazhong, 1968-. “Robust estimation and testing : finite-sample properties and econometric applications.” 2000. Web. 19 Jul 2019.

Vancouver:

You, Jiazhong 1. Robust estimation and testing : finite-sample properties and econometric applications. [Internet] [Doctoral dissertation]. McGill University; 2000. [cited 2019 Jul 19]. Available from: http://digitool.library.mcgill.ca/thesisfile36739.pdf.

Council of Science Editors:

You, Jiazhong 1. Robust estimation and testing : finite-sample properties and econometric applications. [Doctoral Dissertation]. McGill University; 2000. Available from: http://digitool.library.mcgill.ca/thesisfile36739.pdf

Iowa State University

21.
He, Yang.
Three essays on *regression* discontinuity design and partial identification.

Degree: 2018, Iowa State University

URL: https://lib.dr.iastate.edu/etd/16375

► This dissertation consists of three chapters on *regression* discontinuity (RD) design and partial identification, which are widely used techniques in program evaluation. The first and…
(more)

Subjects/Keywords: non-parametric; partial identification; regression discontinuity; robust test; weak identification; Economics

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APA (6^{th} Edition):

He, Y. (2018). Three essays on regression discontinuity design and partial identification. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/16375

Not specified: Masters Thesis or Doctoral Dissertation

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

He, Yang. “Three essays on regression discontinuity design and partial identification.” 2018. Thesis, Iowa State University. Accessed July 19, 2019. https://lib.dr.iastate.edu/etd/16375.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

He, Yang. “Three essays on regression discontinuity design and partial identification.” 2018. Web. 19 Jul 2019.

Vancouver:

He Y. Three essays on regression discontinuity design and partial identification. [Internet] [Thesis]. Iowa State University; 2018. [cited 2019 Jul 19]. Available from: https://lib.dr.iastate.edu/etd/16375.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

He Y. Three essays on regression discontinuity design and partial identification. [Thesis]. Iowa State University; 2018. Available from: https://lib.dr.iastate.edu/etd/16375

Not specified: Masters Thesis or Doctoral Dissertation

22. Kovac, Arne. Wavelet thresholding for unequally time-spaced data.

Degree: PhD, 1999, University of Bristol

URL: http://hdl.handle.net/1983/2088715a-7792-4032-bb76-83e3b0389b94

Subjects/Keywords: 519.5; Adaptive estimation; Robust regression

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APA (6^{th} Edition):

Kovac, A. (1999). Wavelet thresholding for unequally time-spaced data. (Doctoral Dissertation). University of Bristol. Retrieved from http://hdl.handle.net/1983/2088715a-7792-4032-bb76-83e3b0389b94

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

Kovac, Arne. “Wavelet thresholding for unequally time-spaced data.” 1999. Doctoral Dissertation, University of Bristol. Accessed July 19, 2019. http://hdl.handle.net/1983/2088715a-7792-4032-bb76-83e3b0389b94.

MLA Handbook (7^{th} Edition):

Kovac, Arne. “Wavelet thresholding for unequally time-spaced data.” 1999. Web. 19 Jul 2019.

Vancouver:

Kovac A. Wavelet thresholding for unequally time-spaced data. [Internet] [Doctoral dissertation]. University of Bristol; 1999. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/1983/2088715a-7792-4032-bb76-83e3b0389b94.

Council of Science Editors:

Kovac A. Wavelet thresholding for unequally time-spaced data. [Doctoral Dissertation]. University of Bristol; 1999. Available from: http://hdl.handle.net/1983/2088715a-7792-4032-bb76-83e3b0389b94

University of South Africa

23. Burombo, Emmanuel Chamunorwa. Statistical modelling of return on capital employed of individual units.

Degree: 2014, University of South Africa

URL: http://hdl.handle.net/10500/19627

► Return on Capital Employed (ROCE) is a popular financial instrument and communication tool for the appraisal of companies. Often, companies management and other practitioners use…
(more)

Subjects/Keywords: Classical multiple linear regression; Principal components regression; Generalized least squares regression; Robust maximum likelihood regression; Return on capital employed; Stepwise directed search; Kaiser-Guttman criterion; Key determinants

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APA (6^{th} Edition):

Burombo, E. C. (2014). Statistical modelling of return on capital employed of individual units. (Masters Thesis). University of South Africa. Retrieved from http://hdl.handle.net/10500/19627

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

Burombo, Emmanuel Chamunorwa. “Statistical modelling of return on capital employed of individual units.” 2014. Masters Thesis, University of South Africa. Accessed July 19, 2019. http://hdl.handle.net/10500/19627.

MLA Handbook (7^{th} Edition):

Burombo, Emmanuel Chamunorwa. “Statistical modelling of return on capital employed of individual units.” 2014. Web. 19 Jul 2019.

Vancouver:

Burombo EC. Statistical modelling of return on capital employed of individual units. [Internet] [Masters thesis]. University of South Africa; 2014. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10500/19627.

Council of Science Editors:

Burombo EC. Statistical modelling of return on capital employed of individual units. [Masters Thesis]. University of South Africa; 2014. Available from: http://hdl.handle.net/10500/19627

KTH

24. Östlund, Simon. Imputation of Missing Data with Application to Commodity Futures.

Degree: Mathematical Statistics, 2016, KTH

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187459

►

In recent years additional requirements have been imposed on ﬁnancial institutions, including Central Counterparty clearing houses (CCPs), as an attempt to assess quantitative measures… (more)

Subjects/Keywords: Missing Data; Bayesian Statistics; Expectation Conditional Maximization (ECM); Conditional Distribution; Robust Regression; MCMC; Copulas.; Saknad Data; Bayesiansk Statistik; Expectation Conditional Maximization (ECM); Betingad Sannolikhet; Robust Regression; MCMC; Copulas.

Record Details Similar Records

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APA (6^{th} Edition):

Östlund, S. (2016). Imputation of Missing Data with Application to Commodity Futures. (Thesis). KTH. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187459

Not specified: Masters Thesis or Doctoral Dissertation

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

Östlund, Simon. “Imputation of Missing Data with Application to Commodity Futures.” 2016. Thesis, KTH. Accessed July 19, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187459.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Östlund, Simon. “Imputation of Missing Data with Application to Commodity Futures.” 2016. Web. 19 Jul 2019.

Vancouver:

Östlund S. Imputation of Missing Data with Application to Commodity Futures. [Internet] [Thesis]. KTH; 2016. [cited 2019 Jul 19]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187459.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Östlund S. Imputation of Missing Data with Application to Commodity Futures. [Thesis]. KTH; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187459

Not specified: Masters Thesis or Doctoral Dissertation

Virginia Tech

25.
Neugebauer, Shawn Patrick.
* Robust* Analysis of M-Estimators of Nonlinear Models.

Degree: MS, Electrical and Computer Engineering, 1996, Virginia Tech

URL: http://hdl.handle.net/10919/36557

► Estimation of nonlinear models finds applications in every field of engineering and the sciences. Much work has been done to build solid statistical theories for…
(more)

Subjects/Keywords: nonlinear regression; nonlinear model estimation; robust regression

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APA (6^{th} Edition):

Neugebauer, S. P. (1996). Robust Analysis of M-Estimators of Nonlinear Models. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/36557

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

Neugebauer, Shawn Patrick. “Robust Analysis of M-Estimators of Nonlinear Models.” 1996. Masters Thesis, Virginia Tech. Accessed July 19, 2019. http://hdl.handle.net/10919/36557.

MLA Handbook (7^{th} Edition):

Neugebauer, Shawn Patrick. “Robust Analysis of M-Estimators of Nonlinear Models.” 1996. Web. 19 Jul 2019.

Vancouver:

Neugebauer SP. Robust Analysis of M-Estimators of Nonlinear Models. [Internet] [Masters thesis]. Virginia Tech; 1996. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10919/36557.

Council of Science Editors:

Neugebauer SP. Robust Analysis of M-Estimators of Nonlinear Models. [Masters Thesis]. Virginia Tech; 1996. Available from: http://hdl.handle.net/10919/36557

University of Alberta

26.
Daemi, Maryam.
Minimax Design for Approximate Straight Line
* Regression*.

Degree: MS, Department of Mathematical and Statistical Sciences, 2012, University of Alberta

URL: https://era.library.ualberta.ca/files/9k41zf80g

► This dissertation first reviews the construction of an optimal design for a straight linear *regression* model with uncorrelated errors when the experimenter seeks protection against…
(more)

Subjects/Keywords: Robust Optimal Design; A-optimality; E-optimality; Minimax Design; Straight Line Regression

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APA (6^{th} Edition):

Daemi, M. (2012). Minimax Design for Approximate Straight Line Regression. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/9k41zf80g

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

Daemi, Maryam. “Minimax Design for Approximate Straight Line Regression.” 2012. Masters Thesis, University of Alberta. Accessed July 19, 2019. https://era.library.ualberta.ca/files/9k41zf80g.

MLA Handbook (7^{th} Edition):

Daemi, Maryam. “Minimax Design for Approximate Straight Line Regression.” 2012. Web. 19 Jul 2019.

Vancouver:

Daemi M. Minimax Design for Approximate Straight Line Regression. [Internet] [Masters thesis]. University of Alberta; 2012. [cited 2019 Jul 19]. Available from: https://era.library.ualberta.ca/files/9k41zf80g.

Council of Science Editors:

Daemi M. Minimax Design for Approximate Straight Line Regression. [Masters Thesis]. University of Alberta; 2012. Available from: https://era.library.ualberta.ca/files/9k41zf80g

27.
Maravina, Tatiana A.
Tests for Differences between Least Squares and *Robust* *Regression* Parameter Estimates and Related Topics.

Degree: PhD, 2013, University of Washington

URL: http://hdl.handle.net/1773/22431

► At the present time there is no well accepted test for comparing least squares and *robust* linear *regression* coefficient estimates. To fill this gap we…
(more)

Subjects/Keywords: fat tails; intercept bias; MM estimator; robust regression; skewness; test for bias; Statistics; statistics

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APA (6^{th} Edition):

Maravina, T. A. (2013). Tests for Differences between Least Squares and Robust Regression Parameter Estimates and Related Topics. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/22431

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

Maravina, Tatiana A. “Tests for Differences between Least Squares and Robust Regression Parameter Estimates and Related Topics.” 2013. Doctoral Dissertation, University of Washington. Accessed July 19, 2019. http://hdl.handle.net/1773/22431.

MLA Handbook (7^{th} Edition):

Maravina, Tatiana A. “Tests for Differences between Least Squares and Robust Regression Parameter Estimates and Related Topics.” 2013. Web. 19 Jul 2019.

Vancouver:

Maravina TA. Tests for Differences between Least Squares and Robust Regression Parameter Estimates and Related Topics. [Internet] [Doctoral dissertation]. University of Washington; 2013. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/1773/22431.

Council of Science Editors:

Maravina TA. Tests for Differences between Least Squares and Robust Regression Parameter Estimates and Related Topics. [Doctoral Dissertation]. University of Washington; 2013. Available from: http://hdl.handle.net/1773/22431

Princeton University

28.
Zhu, Ziwei.
Distributed and *Robust* Statistical Learning
.

Degree: PhD, 2018, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp01d217qs22x

► Decentralized and corrupted data are nowadays ubiquitous, which impose fundamental challenges for modern statistical analysis. Illustrative examples are massive and decentralized data produced by distributed…
(more)

Subjects/Keywords: distributed learning; high-dimensional statistics; low-rank matrix recovery; principal component analysis; regression; robust statistics

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APA (6^{th} Edition):

Zhu, Z. (2018). Distributed and Robust Statistical Learning . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp01d217qs22x

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

Zhu, Ziwei. “Distributed and Robust Statistical Learning .” 2018. Doctoral Dissertation, Princeton University. Accessed July 19, 2019. http://arks.princeton.edu/ark:/88435/dsp01d217qs22x.

MLA Handbook (7^{th} Edition):

Zhu, Ziwei. “Distributed and Robust Statistical Learning .” 2018. Web. 19 Jul 2019.

Vancouver:

Zhu Z. Distributed and Robust Statistical Learning . [Internet] [Doctoral dissertation]. Princeton University; 2018. [cited 2019 Jul 19]. Available from: http://arks.princeton.edu/ark:/88435/dsp01d217qs22x.

Council of Science Editors:

Zhu Z. Distributed and Robust Statistical Learning . [Doctoral Dissertation]. Princeton University; 2018. Available from: http://arks.princeton.edu/ark:/88435/dsp01d217qs22x

Princeton University

29.
Wang, Yuyan.
* Robust* High-Dimensional

Degree: PhD, 2016, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp019c67wq32b

► High-throughput technologies generate datasets with huge dimensionality, large sample size and heterogeneous noises. Many traditional methods become computationally infeasible or no longer applicable with these…
(more)

Subjects/Keywords: Factor models; High-dimensional linear regression; Mixture modeling of hurricane; Robust methods

Record Details Similar Records

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APA (6^{th} Edition):

Wang, Y. (2016). Robust High-Dimensional Regression and Factor Models . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp019c67wq32b

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

Wang, Yuyan. “Robust High-Dimensional Regression and Factor Models .” 2016. Doctoral Dissertation, Princeton University. Accessed July 19, 2019. http://arks.princeton.edu/ark:/88435/dsp019c67wq32b.

MLA Handbook (7^{th} Edition):

Wang, Yuyan. “Robust High-Dimensional Regression and Factor Models .” 2016. Web. 19 Jul 2019.

Vancouver:

Wang Y. Robust High-Dimensional Regression and Factor Models . [Internet] [Doctoral dissertation]. Princeton University; 2016. [cited 2019 Jul 19]. Available from: http://arks.princeton.edu/ark:/88435/dsp019c67wq32b.

Council of Science Editors:

Wang Y. Robust High-Dimensional Regression and Factor Models . [Doctoral Dissertation]. Princeton University; 2016. Available from: http://arks.princeton.edu/ark:/88435/dsp019c67wq32b

University of Arizona

30. Wang, Zhenrui. Statistical Analysis of Operational Data for Manufacturing System Performance Improvement .

Degree: 2013, University of Arizona

URL: http://hdl.handle.net/10150/301673

► The performance of a manufacturing system relies on its four types of elements: operators, machines, computer system and material handling system. To ensure the performance…
(more)

Subjects/Keywords: Hierarchical clustering; Measurement error; Multiple comparisons; Robust regression; Systems & Industrial Engineering; Expectation-maximization

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APA (6^{th} Edition):

Wang, Z. (2013). Statistical Analysis of Operational Data for Manufacturing System Performance Improvement . (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/301673

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

Wang, Zhenrui. “Statistical Analysis of Operational Data for Manufacturing System Performance Improvement .” 2013. Doctoral Dissertation, University of Arizona. Accessed July 19, 2019. http://hdl.handle.net/10150/301673.

MLA Handbook (7^{th} Edition):

Wang, Zhenrui. “Statistical Analysis of Operational Data for Manufacturing System Performance Improvement .” 2013. Web. 19 Jul 2019.

Vancouver:

Wang Z. Statistical Analysis of Operational Data for Manufacturing System Performance Improvement . [Internet] [Doctoral dissertation]. University of Arizona; 2013. [cited 2019 Jul 19]. Available from: http://hdl.handle.net/10150/301673.

Council of Science Editors:

Wang Z. Statistical Analysis of Operational Data for Manufacturing System Performance Improvement . [Doctoral Dissertation]. University of Arizona; 2013. Available from: http://hdl.handle.net/10150/301673