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- 2010 – 2014 (66)
- 2005 – 2009 (23)
- 2000 – 2004 (12)

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- Texas A&M University (10)
- Virginia Tech (10)

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- PhD (52)
- Docteur es (16)

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University of Texas – Austin

1.
Malloy, Shuling Guo.
*Nonparametric**regression* analysis.

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

URL: http://hdl.handle.net/2152/32497

► *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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/1813/31092

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Rutgers University

3.
Li, Mingyu, 1981-.
* Nonparametric* and semiparametric

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

URL: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052210

►

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

URL: https://etda.libraries.psu.edu/catalog/9833

► *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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: https://curate.nd.edu/show/qz20sq89x8q

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:317684

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: 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

► 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

Record Details Similar Records

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

URL: http://hdl.handle.net/1808/10024

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://handle.unsw.edu.au/1959.4/58446 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46045/SOURCE02?view=true

► 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

Record Details Similar Records

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

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

Degree: PhD, Statistics, 2009, Penn State University

URL: https://etda.libraries.psu.edu/catalog/9798

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

Degree: PhD, Mathematical Science, 2014, Clemson University

URL: https://tigerprints.clemson.edu/all_dissertations/1396

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

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

URL: http://hdl.handle.net/1969.1/155626

► 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

Record Details Similar Records

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

APA (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/1969.1/ETD-TAMU-3075

► 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

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/2078.1/203016

►

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

Record Details Similar Records

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APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://repository.cmu.edu/dissertations/1113

► 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

Record Details Similar Records

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APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: https://doi.org/10.14711/thesis-b1256226 ; http://repository.ust.hk/ir/bitstream/1783.1-62250/1/th_redirect.html

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/2104/9145

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

APA (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

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

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

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: 10.18297/etd/856 ; https://ir.library.louisville.edu/etd/856

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

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

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

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

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APA (6^{th} Edition):

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

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

Kai, Bo. “Robust Nonparametric and Semiparametric Modeling.” 2009. Doctoral Dissertation, Penn State University. Accessed November 11, 2019. https://etda.libraries.psu.edu/catalog/9968.

MLA Handbook (7^{th} 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

URL: https://etda.libraries.psu.edu/catalog/19634

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://www.escholarship.org/uc/item/7rt519fd

► 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 (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/1773/42977

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

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

URL: http://hdl.handle.net/11244/15169

► 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 (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: https://scholarbank.nus.edu.sg/handle/10635/153729

Subjects/Keywords: Model averaging; GEE; nonparametric regression

Record Details Similar Records

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

APA (6^{th} 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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/1928/12844

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

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

URL: http://hdl.handle.net/11299/175554

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/11299/167184

► 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

Record Details Similar Records

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

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

URL: http://hdl.handle.net/1773/43748

► 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 (6^{th} 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 (16^{th} 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 (7^{th} 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

URL: http://hdl.handle.net/2123/9807

► 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 (6^{th} Edition):

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

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} 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.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} 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.

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

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

URL: http://hdl.handle.net/10150/183923

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

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