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You searched for subject:(Nonparametric Regression). Showing records 1 – 30 of 158 total matches.

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University of Texas – Austin

1. Malloy, Shuling Guo. Nonparametric regression analysis.

Degree: MSin Statistics, Statistics, 2015, University of Texas – Austin

Nonparametric regression uses nonparametric and flexible methods in analyzing complex data with unknown regression relationships by imposing minimum assumptions on the regression function. The theory… (more)

Subjects/Keywords: Nonparametric regression

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APA (6th Edition):

Malloy, S. G. (2015). Nonparametric regression analysis. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/32497

Chicago Manual of Style (16th Edition):

Malloy, Shuling Guo. “Nonparametric regression analysis.” 2015. Masters Thesis, University of Texas – Austin. Accessed November 11, 2019. http://hdl.handle.net/2152/32497.

MLA Handbook (7th Edition):

Malloy, Shuling Guo. “Nonparametric regression analysis.” 2015. Web. 11 Nov 2019.

Vancouver:

Malloy SG. Nonparametric regression analysis. [Internet] [Masters thesis]. University of Texas – Austin; 2015. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/2152/32497.

Council of Science Editors:

Malloy SG. Nonparametric regression analysis. [Masters Thesis]. University of Texas – Austin; 2015. Available from: http://hdl.handle.net/2152/32497


Cornell University

2. Xiao, Luo. Topics In Bivariate Spline Smoothing .

Degree: 2012, Cornell University

 Penalized spline methods have been popular since the work of Eilers and Marx (1996). Recent years saw extensive theoretical studies and a wide range of… (more)

Subjects/Keywords: penalized splines; nonparametric regression; smoothing

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APA (6th Edition):

Xiao, L. (2012). Topics In Bivariate Spline Smoothing . (Thesis). Cornell University. Retrieved from http://hdl.handle.net/1813/31092

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):

Xiao, Luo. “Topics In Bivariate Spline Smoothing .” 2012. Thesis, Cornell University. Accessed November 11, 2019. http://hdl.handle.net/1813/31092.

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

MLA Handbook (7th Edition):

Xiao, Luo. “Topics In Bivariate Spline Smoothing .” 2012. Web. 11 Nov 2019.

Vancouver:

Xiao L. Topics In Bivariate Spline Smoothing . [Internet] [Thesis]. Cornell University; 2012. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/1813/31092.

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

Council of Science Editors:

Xiao L. Topics In Bivariate Spline Smoothing . [Thesis]. Cornell University; 2012. Available from: http://hdl.handle.net/1813/31092

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


Rutgers University

3. Li, Mingyu, 1981-. Nonparametric and semiparametric regression, missing data, and related algorithms:.

Degree: PhD, Statistics and Biostatistics, 2010, Rutgers University

This dissertation consists of two chapters: Chapter 1 develops nonparametric and semiparametric regression methodologies which relate the group testing responses to the individual covariates information.… (more)

Subjects/Keywords: Nonparametric statistics; Regression analysis

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APA (6th Edition):

Li, Mingyu, 1. (2010). Nonparametric and semiparametric regression, missing data, and related algorithms:. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052210

Chicago Manual of Style (16th Edition):

Li, Mingyu, 1981-. “Nonparametric and semiparametric regression, missing data, and related algorithms:.” 2010. Doctoral Dissertation, Rutgers University. Accessed November 11, 2019. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052210.

MLA Handbook (7th Edition):

Li, Mingyu, 1981-. “Nonparametric and semiparametric regression, missing data, and related algorithms:.” 2010. Web. 11 Nov 2019.

Vancouver:

Li, Mingyu 1. Nonparametric and semiparametric regression, missing data, and related algorithms:. [Internet] [Doctoral dissertation]. Rutgers University; 2010. [cited 2019 Nov 11]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052210.

Council of Science Editors:

Li, Mingyu 1. Nonparametric and semiparametric regression, missing data, and related algorithms:. [Doctoral Dissertation]. Rutgers University; 2010. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052210


Penn State University

4. Jiang, Yuejiao. Estimation and forecasting methodologies for.

Degree: PhD, Statistics, 2009, Penn State University

Nonparametric regression models have been used to explore features of data. Various estimation procedures have been proposed for estimating nonparametric regression models in the literature.… (more)

Subjects/Keywords: nonparametric regression models; dynamic linear models

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APA (6th Edition):

Jiang, Y. (2009). Estimation and forecasting methodologies for. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9833

Chicago Manual of Style (16th Edition):

Jiang, Yuejiao. “Estimation and forecasting methodologies for.” 2009. Doctoral Dissertation, Penn State University. Accessed November 11, 2019. https://etda.libraries.psu.edu/catalog/9833.

MLA Handbook (7th Edition):

Jiang, Yuejiao. “Estimation and forecasting methodologies for.” 2009. Web. 11 Nov 2019.

Vancouver:

Jiang Y. Estimation and forecasting methodologies for. [Internet] [Doctoral dissertation]. Penn State University; 2009. [cited 2019 Nov 11]. Available from: https://etda.libraries.psu.edu/catalog/9833.

Council of Science Editors:

Jiang Y. Estimation and forecasting methodologies for. [Doctoral Dissertation]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9833


University of Notre Dame

5. Patrick J. Miller. Boosted Decision Trees for Multivariate, Hierarchically Clustered, and Longitudinal Data</h1>.

Degree: PhD, Psychology, 2017, University of Notre Dame

  The problem of finding structure in big data sets is becoming increasingly relevant to psychologists as it becomes easier and cheaper to collect data… (more)

Subjects/Keywords: nonparametric regression; nonlinear; Boosted decision trees

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APA (6th Edition):

Miller, P. J. (2017). Boosted Decision Trees for Multivariate, Hierarchically Clustered, and Longitudinal Data</h1>. (Doctoral Dissertation). University of Notre Dame. Retrieved from https://curate.nd.edu/show/qz20sq89x8q

Chicago Manual of Style (16th Edition):

Miller, Patrick J.. “Boosted Decision Trees for Multivariate, Hierarchically Clustered, and Longitudinal Data</h1>.” 2017. Doctoral Dissertation, University of Notre Dame. Accessed November 11, 2019. https://curate.nd.edu/show/qz20sq89x8q.

MLA Handbook (7th Edition):

Miller, Patrick J.. “Boosted Decision Trees for Multivariate, Hierarchically Clustered, and Longitudinal Data</h1>.” 2017. Web. 11 Nov 2019.

Vancouver:

Miller PJ. Boosted Decision Trees for Multivariate, Hierarchically Clustered, and Longitudinal Data</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2017. [cited 2019 Nov 11]. Available from: https://curate.nd.edu/show/qz20sq89x8q.

Council of Science Editors:

Miller PJ. Boosted Decision Trees for Multivariate, Hierarchically Clustered, and Longitudinal Data</h1>. [Doctoral Dissertation]. University of Notre Dame; 2017. Available from: https://curate.nd.edu/show/qz20sq89x8q


University of Manchester

6. Raza, Ali. Essays on Trade, Growth, and Inequality.

Degree: 2018, University of Manchester

 This thesis explores the role of openness to international trade on economic development, characterised by economic growth and income inequality, across countries. The existing empirical… (more)

Subjects/Keywords: Economic Growth; Income Inequality; Nonlinearities; Nonparametric Regression; Schooling; Threshold Regression; Trade.

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APA (6th Edition):

Raza, A. (2018). Essays on Trade, Growth, and Inequality. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:317684

Chicago Manual of Style (16th Edition):

Raza, Ali. “Essays on Trade, Growth, and Inequality.” 2018. Doctoral Dissertation, University of Manchester. Accessed November 11, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:317684.

MLA Handbook (7th Edition):

Raza, Ali. “Essays on Trade, Growth, and Inequality.” 2018. Web. 11 Nov 2019.

Vancouver:

Raza A. Essays on Trade, Growth, and Inequality. [Internet] [Doctoral dissertation]. University of Manchester; 2018. [cited 2019 Nov 11]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:317684.

Council of Science Editors:

Raza A. Essays on Trade, Growth, and Inequality. [Doctoral Dissertation]. University of Manchester; 2018. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:317684


University of Manchester

7. Raza, Ali. Essays on trade, growth, and inequality.

Degree: PhD, 2019, University of Manchester

 This thesis explores the role of openness to international trade on economic development, characterised by economic growth and income inequality, across countries. The existing empirical… (more)

Subjects/Keywords: Trade; Schooling; Nonparametric Regression; Threshold Regression; Income Inequality; Economic Growth; Nonlinearities

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APA (6th Edition):

Raza, A. (2019). Essays on trade, growth, and inequality. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/essays-on-trade-growth-and-inequality(f6ccf349-f72b-45c5-81ff-ec56c0ebd171).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779646

Chicago Manual of Style (16th Edition):

Raza, Ali. “Essays on trade, growth, and inequality.” 2019. Doctoral Dissertation, University of Manchester. Accessed November 11, 2019. https://www.research.manchester.ac.uk/portal/en/theses/essays-on-trade-growth-and-inequality(f6ccf349-f72b-45c5-81ff-ec56c0ebd171).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779646.

MLA Handbook (7th Edition):

Raza, Ali. “Essays on trade, growth, and inequality.” 2019. Web. 11 Nov 2019.

Vancouver:

Raza A. Essays on trade, growth, and inequality. [Internet] [Doctoral dissertation]. University of Manchester; 2019. [cited 2019 Nov 11]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/essays-on-trade-growth-and-inequality(f6ccf349-f72b-45c5-81ff-ec56c0ebd171).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779646.

Council of Science Editors:

Raza A. Essays on trade, growth, and inequality. [Doctoral Dissertation]. University of Manchester; 2019. Available from: https://www.research.manchester.ac.uk/portal/en/theses/essays-on-trade-growth-and-inequality(f6ccf349-f72b-45c5-81ff-ec56c0ebd171).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779646


University of Kansas

8. Wang, Wenhao. Are All Item Response Functions Monotonically Increasing?.

Degree: PhD, Psychology & Research in Education, 2012, University of Kansas

 Item response functions of the parametric logistic IRT models follow the logistic form which is monotonically increasing. However, item response functions of some real items… (more)

Subjects/Keywords: Educational tests & measurements; B-spline nonparametric irt; Item-ability regression; Model fit; Nonmonotonicity; Nonparametric smooth regression; Posterior predictive model checking

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APA (6th Edition):

Wang, W. (2012). Are All Item Response Functions Monotonically Increasing?. (Doctoral Dissertation). University of Kansas. Retrieved from http://hdl.handle.net/1808/10024

Chicago Manual of Style (16th Edition):

Wang, Wenhao. “Are All Item Response Functions Monotonically Increasing?.” 2012. Doctoral Dissertation, University of Kansas. Accessed November 11, 2019. http://hdl.handle.net/1808/10024.

MLA Handbook (7th Edition):

Wang, Wenhao. “Are All Item Response Functions Monotonically Increasing?.” 2012. Web. 11 Nov 2019.

Vancouver:

Wang W. Are All Item Response Functions Monotonically Increasing?. [Internet] [Doctoral dissertation]. University of Kansas; 2012. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/1808/10024.

Council of Science Editors:

Wang W. Are All Item Response Functions Monotonically Increasing?. [Doctoral Dissertation]. University of Kansas; 2012. Available from: http://hdl.handle.net/1808/10024


University of New South Wales

9. Rodrigues, Thais Carvalho Valadares. Pyramid Quantile Regression.

Degree: Mathematics & Statistics, 2017, University of New South Wales

 Quantile regression models provide a wide picture of the conditional distributions of the response variable by capturing the effect of the covariates at different quantile… (more)

Subjects/Keywords: Crossing quantile regression; Extremal quantile regression; Gaussian process regression; Monotonicity; Nonparametric quantile regression; O'Sullivan penalised splines; Simultaneous quantile regression; O’Sullivan penalised splines , Simultaneous quantile regression; Asymmetric Laplace distribution , Bayesian quantile pyramid , B-Splines , Crossing quantile regression; Extremal quantile regression , Gaussian process regression , Monotonicity , Nonparametric quantile regression

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APA (6th Edition):

Rodrigues, T. C. V. (2017). Pyramid Quantile Regression. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/58446 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46045/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Rodrigues, Thais Carvalho Valadares. “Pyramid Quantile Regression.” 2017. Doctoral Dissertation, University of New South Wales. Accessed November 11, 2019. http://handle.unsw.edu.au/1959.4/58446 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46045/SOURCE02?view=true.

MLA Handbook (7th Edition):

Rodrigues, Thais Carvalho Valadares. “Pyramid Quantile Regression.” 2017. Web. 11 Nov 2019.

Vancouver:

Rodrigues TCV. Pyramid Quantile Regression. [Internet] [Doctoral dissertation]. University of New South Wales; 2017. [cited 2019 Nov 11]. Available from: http://handle.unsw.edu.au/1959.4/58446 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46045/SOURCE02?view=true.

Council of Science Editors:

Rodrigues TCV. Pyramid Quantile Regression. [Doctoral Dissertation]. University of New South Wales; 2017. Available from: http://handle.unsw.edu.au/1959.4/58446 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46045/SOURCE02?view=true


Penn State University

10. Huang, Mian. NONPARAMETRIC TECHNIQUES IN FINITE MIXTURE OF REGRESSION MODELS.

Degree: PhD, Statistics, 2009, Penn State University

 Mixture models have been popular in the literature of both statistics and social science. In this dissertation, we propose a new mixture model, namely, nonparametric(more)

Subjects/Keywords: mixture of regression models; nonparametric regression; EM algorithm; mixture of Gaussian processes

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APA (6th Edition):

Huang, M. (2009). NONPARAMETRIC TECHNIQUES IN FINITE MIXTURE OF REGRESSION MODELS. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/9798

Chicago Manual of Style (16th Edition):

Huang, Mian. “NONPARAMETRIC TECHNIQUES IN FINITE MIXTURE OF REGRESSION MODELS.” 2009. Doctoral Dissertation, Penn State University. Accessed November 11, 2019. https://etda.libraries.psu.edu/catalog/9798.

MLA Handbook (7th Edition):

Huang, Mian. “NONPARAMETRIC TECHNIQUES IN FINITE MIXTURE OF REGRESSION MODELS.” 2009. Web. 11 Nov 2019.

Vancouver:

Huang M. NONPARAMETRIC TECHNIQUES IN FINITE MIXTURE OF REGRESSION MODELS. [Internet] [Doctoral dissertation]. Penn State University; 2009. [cited 2019 Nov 11]. Available from: https://etda.libraries.psu.edu/catalog/9798.

Council of Science Editors:

Huang M. NONPARAMETRIC TECHNIQUES IN FINITE MIXTURE OF REGRESSION MODELS. [Doctoral Dissertation]. Penn State University; 2009. Available from: https://etda.libraries.psu.edu/catalog/9798


Clemson University

11. Wang, Dewei. Nonparametric and semiparametric group testing regression models.

Degree: PhD, Mathematical Science, 2014, Clemson University

  This dissertation consists of three projects in the area of group testing. The method of group testing, through the use of pooling, has proven… (more)

Subjects/Keywords: Group testing; Latent data; Nonparametric regression; Pooled data; Semiparametric regression; Sensitivity and specificity

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APA (6th Edition):

Wang, D. (2014). Nonparametric and semiparametric group testing regression models. (Doctoral Dissertation). Clemson University. Retrieved from https://tigerprints.clemson.edu/all_dissertations/1396

Chicago Manual of Style (16th Edition):

Wang, Dewei. “Nonparametric and semiparametric group testing regression models.” 2014. Doctoral Dissertation, Clemson University. Accessed November 11, 2019. https://tigerprints.clemson.edu/all_dissertations/1396.

MLA Handbook (7th Edition):

Wang, Dewei. “Nonparametric and semiparametric group testing regression models.” 2014. Web. 11 Nov 2019.

Vancouver:

Wang D. Nonparametric and semiparametric group testing regression models. [Internet] [Doctoral dissertation]. Clemson University; 2014. [cited 2019 Nov 11]. Available from: https://tigerprints.clemson.edu/all_dissertations/1396.

Council of Science Editors:

Wang D. Nonparametric and semiparametric group testing regression models. [Doctoral Dissertation]. Clemson University; 2014. Available from: https://tigerprints.clemson.edu/all_dissertations/1396


Texas A&M University

12. Zhang, Nan. Adaptive Basis Sampling for Smoothing Splines.

Degree: 2015, Texas A&M University

 Smoothing splines provide flexible nonparametric regression estimators. Penalized likelihood method is adopted when responses are from exponential families and multivariate models are constructed with certain… (more)

Subjects/Keywords: Nonparametric regression; Penalized likelihood; Reproducing kernel Hilbert space

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APA (6th Edition):

Zhang, N. (2015). Adaptive Basis Sampling for Smoothing Splines. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155626

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):

Zhang, Nan. “Adaptive Basis Sampling for Smoothing Splines.” 2015. Thesis, Texas A&M University. Accessed November 11, 2019. http://hdl.handle.net/1969.1/155626.

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

MLA Handbook (7th Edition):

Zhang, Nan. “Adaptive Basis Sampling for Smoothing Splines.” 2015. Web. 11 Nov 2019.

Vancouver:

Zhang N. Adaptive Basis Sampling for Smoothing Splines. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/1969.1/155626.

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

Council of Science Editors:

Zhang N. Adaptive Basis Sampling for Smoothing Splines. [Thesis]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155626

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


Texas A&M University

13. Maity, Arnab. Efficient inference in general semiparametric regression models.

Degree: 2009, Texas A&M University

 Semiparametric regression has become very popular in the field of Statistics over the years. While on one hand more and more sophisticated models are being… (more)

Subjects/Keywords: Nonparametric/Semiparametric Regression; Kernel Method; Measurement Error; Semiparametric Efficiency; Repeated Measures

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APA (6th Edition):

Maity, A. (2009). Efficient inference in general semiparametric regression models. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-3075

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):

Maity, Arnab. “Efficient inference in general semiparametric regression models.” 2009. Thesis, Texas A&M University. Accessed November 11, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-3075.

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

MLA Handbook (7th Edition):

Maity, Arnab. “Efficient inference in general semiparametric regression models.” 2009. Web. 11 Nov 2019.

Vancouver:

Maity A. Efficient inference in general semiparametric regression models. [Internet] [Thesis]. Texas A&M University; 2009. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-3075.

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

Council of Science Editors:

Maity A. Efficient inference in general semiparametric regression models. [Thesis]. Texas A&M University; 2009. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-3075

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


Université Catholique de Louvain

14. Chau, Van Vinh. Advances in spectral analysis for multivariate, nonstationary and replicated time series.

Degree: 2018, Université Catholique de Louvain

Spectral analysis of time series refers to the analysis of a time series in terms of its Fourier or power spectrum to study cross-dependencies or… (more)

Subjects/Keywords: Fourier Spectrum; Wavelets; Nonparametric Regression; Riemannian manifold; Data Depth; Time Series

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APA (6th Edition):

Chau, V. V. (2018). Advances in spectral analysis for multivariate, nonstationary and replicated time series. (Thesis). Université Catholique de Louvain. Retrieved from http://hdl.handle.net/2078.1/203016

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):

Chau, Van Vinh. “Advances in spectral analysis for multivariate, nonstationary and replicated time series.” 2018. Thesis, Université Catholique de Louvain. Accessed November 11, 2019. http://hdl.handle.net/2078.1/203016.

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

MLA Handbook (7th Edition):

Chau, Van Vinh. “Advances in spectral analysis for multivariate, nonstationary and replicated time series.” 2018. Web. 11 Nov 2019.

Vancouver:

Chau VV. Advances in spectral analysis for multivariate, nonstationary and replicated time series. [Internet] [Thesis]. Université Catholique de Louvain; 2018. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/2078.1/203016.

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

Council of Science Editors:

Chau VV. Advances in spectral analysis for multivariate, nonstationary and replicated time series. [Thesis]. Université Catholique de Louvain; 2018. Available from: http://hdl.handle.net/2078.1/203016

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


Carnegie Mellon University

15. Wang, Yu-Xiang. New Paradigms and Optimality Guarantees in Statistical Learning and Estimation.

Degree: 2017, Carnegie Mellon University

 Machine learning (ML) has become one of the most powerful classes of tools for artificial intelligence, personalized web services and data science problems across fields.… (more)

Subjects/Keywords: machine learning; statistics; differential privacy; nonparametric regression; trend filtering; contextual bandits

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APA (6th Edition):

Wang, Y. (2017). New Paradigms and Optimality Guarantees in Statistical Learning and Estimation. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1113

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):

Wang, Yu-Xiang. “New Paradigms and Optimality Guarantees in Statistical Learning and Estimation.” 2017. Thesis, Carnegie Mellon University. Accessed November 11, 2019. http://repository.cmu.edu/dissertations/1113.

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

MLA Handbook (7th Edition):

Wang, Yu-Xiang. “New Paradigms and Optimality Guarantees in Statistical Learning and Estimation.” 2017. Web. 11 Nov 2019.

Vancouver:

Wang Y. New Paradigms and Optimality Guarantees in Statistical Learning and Estimation. [Internet] [Thesis]. Carnegie Mellon University; 2017. [cited 2019 Nov 11]. Available from: http://repository.cmu.edu/dissertations/1113.

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

Council of Science Editors:

Wang Y. New Paradigms and Optimality Guarantees in Statistical Learning and Estimation. [Thesis]. Carnegie Mellon University; 2017. Available from: http://repository.cmu.edu/dissertations/1113

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


Hong Kong University of Science and Technology

16. Zhang, Hanghui. Essays on semiparametric estimations of the binary choice model and the general heteroskedastic transformation model.

Degree: 2013, Hong Kong University of Science and Technology

 This dissertation focuses on the research on the semiparametric and nonparametric identification and estimation of the binary choice model and the general heteroskedastic transformation regression(more)

Subjects/Keywords: Econometrics; Mathematical models; Nonparametric statistics; Estimation theory; Regression analysis

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APA (6th Edition):

Zhang, H. (2013). Essays on semiparametric estimations of the binary choice model and the general heteroskedastic transformation model. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1256226 ; http://repository.ust.hk/ir/bitstream/1783.1-62250/1/th_redirect.html

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):

Zhang, Hanghui. “Essays on semiparametric estimations of the binary choice model and the general heteroskedastic transformation model.” 2013. Thesis, Hong Kong University of Science and Technology. Accessed November 11, 2019. https://doi.org/10.14711/thesis-b1256226 ; http://repository.ust.hk/ir/bitstream/1783.1-62250/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Zhang, Hanghui. “Essays on semiparametric estimations of the binary choice model and the general heteroskedastic transformation model.” 2013. Web. 11 Nov 2019.

Vancouver:

Zhang H. Essays on semiparametric estimations of the binary choice model and the general heteroskedastic transformation model. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2013. [cited 2019 Nov 11]. Available from: https://doi.org/10.14711/thesis-b1256226 ; http://repository.ust.hk/ir/bitstream/1783.1-62250/1/th_redirect.html.

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

Council of Science Editors:

Zhang H. Essays on semiparametric estimations of the binary choice model and the general heteroskedastic transformation model. [Thesis]. Hong Kong University of Science and Technology; 2013. Available from: https://doi.org/10.14711/thesis-b1256226 ; http://repository.ust.hk/ir/bitstream/1783.1-62250/1/th_redirect.html

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


Baylor University

17. Buros, Amy. Semiparametric AUC regression for ordered treatment effects.

Degree: Statistical Sciences., 2014, Baylor University

 We investigated distribution free methods for testing covariate adjusted treatment effects when the researchers believe that these effects are ordered. Dodd and Pepe (2003) proposed… (more)

Subjects/Keywords: Jonckheere-Terpstra statistic.; Nonparametric statistics.; AUC regression.; Covariate adjusted treatment effects.

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APA (6th Edition):

Buros, A. (2014). Semiparametric AUC regression for ordered treatment effects. (Thesis). Baylor University. Retrieved from http://hdl.handle.net/2104/9145

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):

Buros, Amy. “Semiparametric AUC regression for ordered treatment effects. ” 2014. Thesis, Baylor University. Accessed November 11, 2019. http://hdl.handle.net/2104/9145.

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

MLA Handbook (7th Edition):

Buros, Amy. “Semiparametric AUC regression for ordered treatment effects. ” 2014. Web. 11 Nov 2019.

Vancouver:

Buros A. Semiparametric AUC regression for ordered treatment effects. [Internet] [Thesis]. Baylor University; 2014. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/2104/9145.

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

Council of Science Editors:

Buros A. Semiparametric AUC regression for ordered treatment effects. [Thesis]. Baylor University; 2014. Available from: http://hdl.handle.net/2104/9145

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


University of Louisville

18. Lorenz, Douglas J. Marginal nonparametric inference for waiting times in multistage models : hypothesis testing and regression.

Degree: PhD, 2011, University of Louisville

 Marginal inference for waiting times in multi-stage time-to-event models is complicated by right censoring of observations as well as the prior history of events in… (more)

Subjects/Keywords: Survival analysis; Hypothesis testing; Multi-stage models; Regression; Nonparametric inference

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APA (6th Edition):

Lorenz, D. J. (2011). Marginal nonparametric inference for waiting times in multistage models : hypothesis testing and regression. (Doctoral Dissertation). University of Louisville. Retrieved from 10.18297/etd/856 ; https://ir.library.louisville.edu/etd/856

Chicago Manual of Style (16th Edition):

Lorenz, Douglas J. “Marginal nonparametric inference for waiting times in multistage models : hypothesis testing and regression.” 2011. Doctoral Dissertation, University of Louisville. Accessed November 11, 2019. 10.18297/etd/856 ; https://ir.library.louisville.edu/etd/856.

MLA Handbook (7th Edition):

Lorenz, Douglas J. “Marginal nonparametric inference for waiting times in multistage models : hypothesis testing and regression.” 2011. Web. 11 Nov 2019.

Vancouver:

Lorenz DJ. Marginal nonparametric inference for waiting times in multistage models : hypothesis testing and regression. [Internet] [Doctoral dissertation]. University of Louisville; 2011. [cited 2019 Nov 11]. Available from: 10.18297/etd/856 ; https://ir.library.louisville.edu/etd/856.

Council of Science Editors:

Lorenz DJ. Marginal nonparametric inference for waiting times in multistage models : hypothesis testing and regression. [Doctoral Dissertation]. University of Louisville; 2011. Available from: 10.18297/etd/856 ; https://ir.library.louisville.edu/etd/856


Penn State University

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

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 November 11, 2019. https://etda.libraries.psu.edu/catalog/9968.

MLA Handbook (7th Edition):

Kai, Bo. “Robust Nonparametric and Semiparametric Modeling.” 2009. Web. 11 Nov 2019.

Vancouver:

Kai B. Robust Nonparametric and Semiparametric Modeling. [Internet] [Doctoral dissertation]. Penn State University; 2009. [cited 2019 Nov 11]. 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

20. Lou, Lejia. Thresholded partial correlation approach for variable selection in linear models and partially linear models.

Degree: PhD, Statistics, 2013, Penn State University

 This thesis is concerned with variable selection in linear models and partially linear models for high-dimensional data analysis. With the development of technology, it is… (more)

Subjects/Keywords: Variable Selection; Linear Model; Partially Linear Model; Nonparametric Regression

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

APA (6th Edition):

Lou, L. (2013). Thresholded partial correlation approach for variable selection in linear models and partially linear models. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/19634

Chicago Manual of Style (16th Edition):

Lou, Lejia. “Thresholded partial correlation approach for variable selection in linear models and partially linear models.” 2013. Doctoral Dissertation, Penn State University. Accessed November 11, 2019. https://etda.libraries.psu.edu/catalog/19634.

MLA Handbook (7th Edition):

Lou, Lejia. “Thresholded partial correlation approach for variable selection in linear models and partially linear models.” 2013. Web. 11 Nov 2019.

Vancouver:

Lou L. Thresholded partial correlation approach for variable selection in linear models and partially linear models. [Internet] [Doctoral dissertation]. Penn State University; 2013. [cited 2019 Nov 11]. Available from: https://etda.libraries.psu.edu/catalog/19634.

Council of Science Editors:

Lou L. Thresholded partial correlation approach for variable selection in linear models and partially linear models. [Doctoral Dissertation]. Penn State University; 2013. Available from: https://etda.libraries.psu.edu/catalog/19634


University of California – Berkeley

21. Huoh, Yu-Jay. Sensitivity Analysis of Stochastic Simulators with Information Theory.

Degree: Statistics, 2013, University of California – Berkeley

 The increased computational power available today has made the use of computer models or simulators common in many fields. While there is a widely adopted… (more)

Subjects/Keywords: Statistics; Bayesian nonparametric density regression; information theory; sensitivity analysis; uncertainty quantification

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APA (6th Edition):

Huoh, Y. (2013). Sensitivity Analysis of Stochastic Simulators with Information Theory. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/7rt519fd

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):

Huoh, Yu-Jay. “Sensitivity Analysis of Stochastic Simulators with Information Theory.” 2013. Thesis, University of California – Berkeley. Accessed November 11, 2019. http://www.escholarship.org/uc/item/7rt519fd.

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

MLA Handbook (7th Edition):

Huoh, Yu-Jay. “Sensitivity Analysis of Stochastic Simulators with Information Theory.” 2013. Web. 11 Nov 2019.

Vancouver:

Huoh Y. Sensitivity Analysis of Stochastic Simulators with Information Theory. [Internet] [Thesis]. University of California – Berkeley; 2013. [cited 2019 Nov 11]. Available from: http://www.escholarship.org/uc/item/7rt519fd.

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

Council of Science Editors:

Huoh Y. Sensitivity Analysis of Stochastic Simulators with Information Theory. [Thesis]. University of California – Berkeley; 2013. Available from: http://www.escholarship.org/uc/item/7rt519fd

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


University of Washington

22. Ortiz, Brayan. A Finite Approximation Framework for Infinite Dimensional Functional Problems.

Degree: PhD, 2018, University of Washington

 It is often of interest to non-parametrically estimate regression functions. Penalized regression (PR) is one effective, well-studied solution to this problem. Unfortunately, in many cases,… (more)

Subjects/Keywords: denoising; functional estimation; machine learning; nonparametric regression; total variation; Biostatistics; Biostatistics

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APA (6th Edition):

Ortiz, B. (2018). A Finite Approximation Framework for Infinite Dimensional Functional Problems. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/42977

Chicago Manual of Style (16th Edition):

Ortiz, Brayan. “A Finite Approximation Framework for Infinite Dimensional Functional Problems.” 2018. Doctoral Dissertation, University of Washington. Accessed November 11, 2019. http://hdl.handle.net/1773/42977.

MLA Handbook (7th Edition):

Ortiz, Brayan. “A Finite Approximation Framework for Infinite Dimensional Functional Problems.” 2018. Web. 11 Nov 2019.

Vancouver:

Ortiz B. A Finite Approximation Framework for Infinite Dimensional Functional Problems. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/1773/42977.

Council of Science Editors:

Ortiz B. A Finite Approximation Framework for Infinite Dimensional Functional Problems. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/42977


Oklahoma State University

23. Wang, Ningning. Nonparametric Empirical Likelihood Density Functionals Estimation and Applications.

Degree: Statistics, 2013, Oklahoma State University

 Chapter 2 of this dissertation presents a nonparametric empirical likelihood estimation of kernel density functionals (ELKDFE), which are constructed based on a kernel density functional… (more)

Subjects/Keywords: cumulative distribution function; empirical likelihood; kernel density functionals; nonparametric regression

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APA (6th Edition):

Wang, N. (2013). Nonparametric Empirical Likelihood Density Functionals Estimation and Applications. (Thesis). Oklahoma State University. Retrieved from http://hdl.handle.net/11244/15169

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):

Wang, Ningning. “Nonparametric Empirical Likelihood Density Functionals Estimation and Applications.” 2013. Thesis, Oklahoma State University. Accessed November 11, 2019. http://hdl.handle.net/11244/15169.

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

MLA Handbook (7th Edition):

Wang, Ningning. “Nonparametric Empirical Likelihood Density Functionals Estimation and Applications.” 2013. Web. 11 Nov 2019.

Vancouver:

Wang N. Nonparametric Empirical Likelihood Density Functionals Estimation and Applications. [Internet] [Thesis]. Oklahoma State University; 2013. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/11244/15169.

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

Council of Science Editors:

Wang N. Nonparametric Empirical Likelihood Density Functionals Estimation and Applications. [Thesis]. Oklahoma State University; 2013. Available from: http://hdl.handle.net/11244/15169

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

24. WANG JINGLI. MODEL AVERAGING FOR LONGITUDINAL COVARIANCE ESTIMATION AND BAYESIAN NONPARAMETRIC RGRESSION.

Degree: 2019, National University of Singapore

Subjects/Keywords: Model averaging; GEE; nonparametric regression

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APA (6th Edition):

JINGLI, W. (2019). MODEL AVERAGING FOR LONGITUDINAL COVARIANCE ESTIMATION AND BAYESIAN NONPARAMETRIC RGRESSION. (Thesis). National University of Singapore. Retrieved from https://scholarbank.nus.edu.sg/handle/10635/153729

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):

JINGLI, WANG. “MODEL AVERAGING FOR LONGITUDINAL COVARIANCE ESTIMATION AND BAYESIAN NONPARAMETRIC RGRESSION.” 2019. Thesis, National University of Singapore. Accessed November 11, 2019. https://scholarbank.nus.edu.sg/handle/10635/153729.

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

MLA Handbook (7th Edition):

JINGLI, WANG. “MODEL AVERAGING FOR LONGITUDINAL COVARIANCE ESTIMATION AND BAYESIAN NONPARAMETRIC RGRESSION.” 2019. Web. 11 Nov 2019.

Vancouver:

JINGLI W. MODEL AVERAGING FOR LONGITUDINAL COVARIANCE ESTIMATION AND BAYESIAN NONPARAMETRIC RGRESSION. [Internet] [Thesis]. National University of Singapore; 2019. [cited 2019 Nov 11]. Available from: https://scholarbank.nus.edu.sg/handle/10635/153729.

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

Council of Science Editors:

JINGLI W. MODEL AVERAGING FOR LONGITUDINAL COVARIANCE ESTIMATION AND BAYESIAN NONPARAMETRIC RGRESSION. [Thesis]. National University of Singapore; 2019. Available from: https://scholarbank.nus.edu.sg/handle/10635/153729

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


University of New Mexico

25. Nosedal-Sanchez, Alvaro. Adaptive weighting for flexible estimation in nonparametric regression models.

Degree: Mathematics & Statistics, 2011, University of New Mexico

 We propose a new method to find spatially adaptive smoothing splines. This new method breaks down the interval [0, 1] into p disjoint sub-intervals. Then… (more)

Subjects/Keywords: Smoothing (Statistics); Estimation theory; Regression analysis; Nonparametric statistics.

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APA (6th Edition):

Nosedal-Sanchez, A. (2011). Adaptive weighting for flexible estimation in nonparametric regression models. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/12844

Chicago Manual of Style (16th Edition):

Nosedal-Sanchez, Alvaro. “Adaptive weighting for flexible estimation in nonparametric regression models.” 2011. Doctoral Dissertation, University of New Mexico. Accessed November 11, 2019. http://hdl.handle.net/1928/12844.

MLA Handbook (7th Edition):

Nosedal-Sanchez, Alvaro. “Adaptive weighting for flexible estimation in nonparametric regression models.” 2011. Web. 11 Nov 2019.

Vancouver:

Nosedal-Sanchez A. Adaptive weighting for flexible estimation in nonparametric regression models. [Internet] [Doctoral dissertation]. University of New Mexico; 2011. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/1928/12844.

Council of Science Editors:

Nosedal-Sanchez A. Adaptive weighting for flexible estimation in nonparametric regression models. [Doctoral Dissertation]. University of New Mexico; 2011. Available from: http://hdl.handle.net/1928/12844


University of Minnesota

26. Wang, Xu. Searching, Clustering and Regression on non-Euclidean Spaces.

Degree: PhD, Mathematics, 2015, University of Minnesota

 This dissertation considers three common tasks (e.g., searching, clustering, regression) over Riemannian spaces. The first task considers the problem of efficiently deciding which of a… (more)

Subjects/Keywords: Bayesian; Clustering; Fast search; Manifold; Nonparametric regression; Spectral clustering

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APA (6th Edition):

Wang, X. (2015). Searching, Clustering and Regression on non-Euclidean Spaces. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/175554

Chicago Manual of Style (16th Edition):

Wang, Xu. “Searching, Clustering and Regression on non-Euclidean Spaces.” 2015. Doctoral Dissertation, University of Minnesota. Accessed November 11, 2019. http://hdl.handle.net/11299/175554.

MLA Handbook (7th Edition):

Wang, Xu. “Searching, Clustering and Regression on non-Euclidean Spaces.” 2015. Web. 11 Nov 2019.

Vancouver:

Wang X. Searching, Clustering and Regression on non-Euclidean Spaces. [Internet] [Doctoral dissertation]. University of Minnesota; 2015. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/11299/175554.

Council of Science Editors:

Wang X. Searching, Clustering and Regression on non-Euclidean Spaces. [Doctoral Dissertation]. University of Minnesota; 2015. Available from: http://hdl.handle.net/11299/175554


University of Minnesota

27. Kang, Yicheng. Edge detection and image restoration of blurred noisy images using jump regression analysis.

Degree: PhD, Statistics, 2013, University of Minnesota

 We consider the problem of edge-preserving image restoration when images are degraded by spatial blur and pointwise noise. When the spatial blur described by a… (more)

Subjects/Keywords: Blind image deblurring; Denoising; Edges; Nonparametric regression; Smoothing; Surface estimation; Statistics

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

APA (6th Edition):

Kang, Y. (2013). Edge detection and image restoration of blurred noisy images using jump regression analysis. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/167184

Chicago Manual of Style (16th Edition):

Kang, Yicheng. “Edge detection and image restoration of blurred noisy images using jump regression analysis.” 2013. Doctoral Dissertation, University of Minnesota. Accessed November 11, 2019. http://hdl.handle.net/11299/167184.

MLA Handbook (7th Edition):

Kang, Yicheng. “Edge detection and image restoration of blurred noisy images using jump regression analysis.” 2013. Web. 11 Nov 2019.

Vancouver:

Kang Y. Edge detection and image restoration of blurred noisy images using jump regression analysis. [Internet] [Doctoral dissertation]. University of Minnesota; 2013. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/11299/167184.

Council of Science Editors:

Kang Y. Edge detection and image restoration of blurred noisy images using jump regression analysis. [Doctoral Dissertation]. University of Minnesota; 2013. Available from: http://hdl.handle.net/11299/167184


University of Washington

28. Mohammed, Kitty. Statistical Methods for Manifold Recovery and C^{1, 1} Regression on Manifolds.

Degree: PhD, 2019, University of Washington

 High-dimensional data sets often have lower-dimensional structure taking the form of a submanifold of a Euclidean space. It is challenging but necessary to develop statistical… (more)

Subjects/Keywords: machine learning; manifold learning; nonparametric regression; statistics; Statistics; Statistics

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

APA (6th Edition):

Mohammed, K. (2019). Statistical Methods for Manifold Recovery and C^{1, 1} Regression on Manifolds. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43748

Chicago Manual of Style (16th Edition):

Mohammed, Kitty. “Statistical Methods for Manifold Recovery and C^{1, 1} Regression on Manifolds.” 2019. Doctoral Dissertation, University of Washington. Accessed November 11, 2019. http://hdl.handle.net/1773/43748.

MLA Handbook (7th Edition):

Mohammed, Kitty. “Statistical Methods for Manifold Recovery and C^{1, 1} Regression on Manifolds.” 2019. Web. 11 Nov 2019.

Vancouver:

Mohammed K. Statistical Methods for Manifold Recovery and C^{1, 1} Regression on Manifolds. [Internet] [Doctoral dissertation]. University of Washington; 2019. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/1773/43748.

Council of Science Editors:

Mohammed K. Statistical Methods for Manifold Recovery and C^{1, 1} Regression on Manifolds. [Doctoral Dissertation]. University of Washington; 2019. Available from: http://hdl.handle.net/1773/43748


University of Sydney

29. Chan, Nigel Hiu Ngai. Uniform convergence on cointegrating regression .

Degree: 2013, University of Sydney

 Nonlinear cointegration model has been a popular tool for applied econometric modelling. There are numerous real life time series examples that demonstrate nonlinear response to… (more)

Subjects/Keywords: Cointegration; uniform convergence; nonparametric regression; kernel estimation; nonstationarity; nonlinearity

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APA (6th Edition):

Chan, N. H. N. (2013). Uniform convergence on cointegrating regression . (Thesis). University of Sydney. Retrieved from http://hdl.handle.net/2123/9807

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):

Chan, Nigel Hiu Ngai. “Uniform convergence on cointegrating regression .” 2013. Thesis, University of Sydney. Accessed November 11, 2019. http://hdl.handle.net/2123/9807.

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

MLA Handbook (7th Edition):

Chan, Nigel Hiu Ngai. “Uniform convergence on cointegrating regression .” 2013. Web. 11 Nov 2019.

Vancouver:

Chan NHN. Uniform convergence on cointegrating regression . [Internet] [Thesis]. University of Sydney; 2013. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/2123/9807.

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

Council of Science Editors:

Chan NHN. Uniform convergence on cointegrating regression . [Thesis]. University of Sydney; 2013. Available from: http://hdl.handle.net/2123/9807

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


University of Arizona

30. RUTHERFORD, BRIAN MILNE. BOOTSTRAP AND RELATED METHODS FOR APPROXIMATE CONFIDENCE BOUNDS IN NONPARAMETRIC REGRESSION.

Degree: 1986, University of Arizona

 The problem considered relates to estimating an arbitrary regression function m(x) from sample pairs (Xᵢ,Yᵢ) 1 ≤ i ≤ n. A model is assumed of… (more)

Subjects/Keywords: Regression analysis.; Nonparametric statistics.

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APA (6th Edition):

RUTHERFORD, B. M. (1986). BOOTSTRAP AND RELATED METHODS FOR APPROXIMATE CONFIDENCE BOUNDS IN NONPARAMETRIC REGRESSION. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/183923

Chicago Manual of Style (16th Edition):

RUTHERFORD, BRIAN MILNE. “BOOTSTRAP AND RELATED METHODS FOR APPROXIMATE CONFIDENCE BOUNDS IN NONPARAMETRIC REGRESSION. ” 1986. Doctoral Dissertation, University of Arizona. Accessed November 11, 2019. http://hdl.handle.net/10150/183923.

MLA Handbook (7th Edition):

RUTHERFORD, BRIAN MILNE. “BOOTSTRAP AND RELATED METHODS FOR APPROXIMATE CONFIDENCE BOUNDS IN NONPARAMETRIC REGRESSION. ” 1986. Web. 11 Nov 2019.

Vancouver:

RUTHERFORD BM. BOOTSTRAP AND RELATED METHODS FOR APPROXIMATE CONFIDENCE BOUNDS IN NONPARAMETRIC REGRESSION. [Internet] [Doctoral dissertation]. University of Arizona; 1986. [cited 2019 Nov 11]. Available from: http://hdl.handle.net/10150/183923.

Council of Science Editors:

RUTHERFORD BM. BOOTSTRAP AND RELATED METHODS FOR APPROXIMATE CONFIDENCE BOUNDS IN NONPARAMETRIC REGRESSION. [Doctoral Dissertation]. University of Arizona; 1986. Available from: http://hdl.handle.net/10150/183923

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