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You searched for subject:(Robust regression). Showing records 1 – 30 of 90 total matches.

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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

 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 (6th 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 (16th 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 (7th 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 regression.

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

 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 (6th Edition):

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

Chicago Manual of Style (16th Edition):

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

MLA Handbook (7th 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

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 (6th 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 (16th 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 (7th 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

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

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

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

 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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

  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 (6th 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 (16th 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 (7th 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

 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 (6th 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/

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

Chicago Manual of Style (16th Edition):

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/.

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

MLA Handbook (7th 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/.

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

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


University of California – San Diego

8. Liu, Jing. Robust PCA and Robust Linear Regression via Sparsity Regularization.

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

 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 (6th 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

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

Chicago Manual of Style (16th Edition):

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.

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

MLA Handbook (7th 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.

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

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

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 (6th 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

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

Chicago Manual of Style (16th Edition):

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.

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

MLA Handbook (7th 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.

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

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

10. Wei, Yan. Robust mixture regression models using t-distribution.

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

 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)

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APA (6th 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 (16th 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 (7th 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 regression models with minimal assumptions / M.M. van der Westhuizen .

Degree: 2011, North-West University

 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 (6th 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

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

Chicago Manual of Style (16th Edition):

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.

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

MLA Handbook (7th 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.

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

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

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

Degree: 1999, University of Bristol

Subjects/Keywords: 519.5; Adaptive estimation; Robust regression

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APA (6th 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 (16th 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 (7th 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 Regression Models.

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

 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

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APA (6th 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 (16th 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 (7th 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 Regression and its Application in Data-driven Modeling and Optimization.

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

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

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

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Ranjan, Rishik. “Robust Gaussian Process Regression and its Application in Data-driven Modeling and Optimization.” 2015. Masters Thesis, University of Alberta. Accessed July 19, 2019. https://era.library.ualberta.ca/files/b2773z58w.

MLA Handbook (7th Edition):

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

 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 (6th 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

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

Chicago Manual of Style (16th Edition):

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.

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

MLA Handbook (7th 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.

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

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


NSYSU

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

Degree: Master, Electrical Engineering, 2008, NSYSU

 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 (6th 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

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

Chicago Manual of Style (16th Edition):

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.

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

MLA Handbook (7th 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.

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

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

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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

 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 (6th 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

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

Chicago Manual of Style (16th Edition):

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.

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

MLA Handbook (7th 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.

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

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

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

Degree: PhD, 1999, University of Bristol

Subjects/Keywords: 519.5; Adaptive estimation; Robust regression

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APA (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

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.

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APA (6th 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

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

Chicago Manual of Style (16th Edition):

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.

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

MLA Handbook (7th 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.

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

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

 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 (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

 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

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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 Regression and Factor Models .

Degree: PhD, 2016, Princeton University

 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

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APA (6th 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 (16th 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 (7th 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

 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 (6th 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 (16th 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 (7th 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

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