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You searched for subject:(Functional Data). Showing records 1 – 30 of 333 total matches.

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University of Minnesota

1. Mallik, Abhirup. Topics in Functional Data Analysis.

Degree: PhD, Statistics, 2017, University of Minnesota

 It is common for modern applications to collect data continuously from a process over a time period. Such data sets can be conceptualized as a… (more)

Subjects/Keywords: Statistics; Functional Data

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APA (6th Edition):

Mallik, A. (2017). Topics in Functional Data Analysis. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/206221

Chicago Manual of Style (16th Edition):

Mallik, Abhirup. “Topics in Functional Data Analysis.” 2017. Doctoral Dissertation, University of Minnesota. Accessed November 28, 2020. http://hdl.handle.net/11299/206221.

MLA Handbook (7th Edition):

Mallik, Abhirup. “Topics in Functional Data Analysis.” 2017. Web. 28 Nov 2020.

Vancouver:

Mallik A. Topics in Functional Data Analysis. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/11299/206221.

Council of Science Editors:

Mallik A. Topics in Functional Data Analysis. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/206221


Anna University

2. Amshakala K. Information theory based data dependency extraction and its application in data integration;.

Degree: Information theory based data dependency extraction and its application in data integration, 2015, Anna University

As a huge volume of data is getting generated every day data integration becomes important to provide a uniform view over the data collected from… (more)

Subjects/Keywords: Data integration; Fuzzy functional dependencies

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APA (6th Edition):

K, A. (2015). Information theory based data dependency extraction and its application in data integration;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/54547

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):

K, Amshakala. “Information theory based data dependency extraction and its application in data integration;.” 2015. Thesis, Anna University. Accessed November 28, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/54547.

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

MLA Handbook (7th Edition):

K, Amshakala. “Information theory based data dependency extraction and its application in data integration;.” 2015. Web. 28 Nov 2020.

Vancouver:

K A. Information theory based data dependency extraction and its application in data integration;. [Internet] [Thesis]. Anna University; 2015. [cited 2020 Nov 28]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/54547.

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

Council of Science Editors:

K A. Information theory based data dependency extraction and its application in data integration;. [Thesis]. Anna University; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/54547

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


Cornell University

3. Earls, Cecilia. Bayesian Hierarchical Gaussian Process Models For Functional Data Analysis.

Degree: PhD, Statistics, 2014, Cornell University

 This dissertation encompasses a breadth of topics in the area of functional data analysis where each function is modeled as a Gaussian process within the… (more)

Subjects/Keywords: Functional data; registration; Covariance estimation

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APA (6th Edition):

Earls, C. (2014). Bayesian Hierarchical Gaussian Process Models For Functional Data Analysis. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/38765

Chicago Manual of Style (16th Edition):

Earls, Cecilia. “Bayesian Hierarchical Gaussian Process Models For Functional Data Analysis.” 2014. Doctoral Dissertation, Cornell University. Accessed November 28, 2020. http://hdl.handle.net/1813/38765.

MLA Handbook (7th Edition):

Earls, Cecilia. “Bayesian Hierarchical Gaussian Process Models For Functional Data Analysis.” 2014. Web. 28 Nov 2020.

Vancouver:

Earls C. Bayesian Hierarchical Gaussian Process Models For Functional Data Analysis. [Internet] [Doctoral dissertation]. Cornell University; 2014. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1813/38765.

Council of Science Editors:

Earls C. Bayesian Hierarchical Gaussian Process Models For Functional Data Analysis. [Doctoral Dissertation]. Cornell University; 2014. Available from: http://hdl.handle.net/1813/38765


Penn State University

4. Das, Kiranmoy. SEMI-PARAMETRIC BAYESIAN FUNCTIONAL MAPPING WITH IRREGULAR SPARSE LONGITUDINAL DATA.

Degree: 2011, Penn State University

 Genome-wide Association Studies, popularly known as GWAS, are playing a key role in understanding the genetic patterns of various traits and diseases. Despite the potential… (more)

Subjects/Keywords: Longitudinal data; functional mapping; MCMC

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APA (6th Edition):

Das, K. (2011). SEMI-PARAMETRIC BAYESIAN FUNCTIONAL MAPPING WITH IRREGULAR SPARSE LONGITUDINAL DATA. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/12109

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):

Das, Kiranmoy. “SEMI-PARAMETRIC BAYESIAN FUNCTIONAL MAPPING WITH IRREGULAR SPARSE LONGITUDINAL DATA.” 2011. Thesis, Penn State University. Accessed November 28, 2020. https://submit-etda.libraries.psu.edu/catalog/12109.

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

MLA Handbook (7th Edition):

Das, Kiranmoy. “SEMI-PARAMETRIC BAYESIAN FUNCTIONAL MAPPING WITH IRREGULAR SPARSE LONGITUDINAL DATA.” 2011. Web. 28 Nov 2020.

Vancouver:

Das K. SEMI-PARAMETRIC BAYESIAN FUNCTIONAL MAPPING WITH IRREGULAR SPARSE LONGITUDINAL DATA. [Internet] [Thesis]. Penn State University; 2011. [cited 2020 Nov 28]. Available from: https://submit-etda.libraries.psu.edu/catalog/12109.

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

Council of Science Editors:

Das K. SEMI-PARAMETRIC BAYESIAN FUNCTIONAL MAPPING WITH IRREGULAR SPARSE LONGITUDINAL DATA. [Thesis]. Penn State University; 2011. Available from: https://submit-etda.libraries.psu.edu/catalog/12109

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


King Abdullah University of Science and Technology

5. Meng, Rui. Growth Curve Analysis and Change-Points Detection in Extremes.

Degree: 2016, King Abdullah University of Science and Technology

 The thesis consists of two coherent projects. The first project presents the results of evaluating salinity tolerance in barley using growth curve analysis where different… (more)

Subjects/Keywords: functional data; fitting; functional data registration; ANOVA model; algorithm; EM

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APA (6th Edition):

Meng, R. (2016). Growth Curve Analysis and Change-Points Detection in Extremes. (Thesis). King Abdullah University of Science and Technology. Retrieved from http://hdl.handle.net/10754/609833

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):

Meng, Rui. “Growth Curve Analysis and Change-Points Detection in Extremes.” 2016. Thesis, King Abdullah University of Science and Technology. Accessed November 28, 2020. http://hdl.handle.net/10754/609833.

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

MLA Handbook (7th Edition):

Meng, Rui. “Growth Curve Analysis and Change-Points Detection in Extremes.” 2016. Web. 28 Nov 2020.

Vancouver:

Meng R. Growth Curve Analysis and Change-Points Detection in Extremes. [Internet] [Thesis]. King Abdullah University of Science and Technology; 2016. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/10754/609833.

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

Council of Science Editors:

Meng R. Growth Curve Analysis and Change-Points Detection in Extremes. [Thesis]. King Abdullah University of Science and Technology; 2016. Available from: http://hdl.handle.net/10754/609833

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


University of Southern California

6. Qiao, Xinghao. Sparseness in functional data analysis.

Degree: PhD, Business Administration, 2015, University of Southern California

Functional Data Analysis (FDA), a branch of statistics that analyzes data providing information about functions measured over some domain, has recently attracted more attention. In… (more)

Subjects/Keywords: functional regression; sparsely sampled functional data; high dimensional functional data; graphical models; features screening

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APA (6th Edition):

Qiao, X. (2015). Sparseness in functional data analysis. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/621510/rec/5981

Chicago Manual of Style (16th Edition):

Qiao, Xinghao. “Sparseness in functional data analysis.” 2015. Doctoral Dissertation, University of Southern California. Accessed November 28, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/621510/rec/5981.

MLA Handbook (7th Edition):

Qiao, Xinghao. “Sparseness in functional data analysis.” 2015. Web. 28 Nov 2020.

Vancouver:

Qiao X. Sparseness in functional data analysis. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2020 Nov 28]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/621510/rec/5981.

Council of Science Editors:

Qiao X. Sparseness in functional data analysis. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/621510/rec/5981


UCLA

7. Zhang, Yafeng. Clustering and Registration of Functional Data with Applications in Time Course Genomics Data.

Degree: Biostatistics, 2014, UCLA

Functional data analysis aims to provide statistical inference for stochastic processes defined over a functional space. Typical data sources, often modeled using functional data analytic… (more)

Subjects/Keywords: Biostatistics; Statistics; Bioinformatics; Dirichlet Process; Functional Data Analysis; Functional Data Clustering; Functional Data Registration; Joint Modelling; Time Course Genomics Data

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APA (6th Edition):

Zhang, Y. (2014). Clustering and Registration of Functional Data with Applications in Time Course Genomics Data. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/0d01t79f

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, Yafeng. “Clustering and Registration of Functional Data with Applications in Time Course Genomics Data.” 2014. Thesis, UCLA. Accessed November 28, 2020. http://www.escholarship.org/uc/item/0d01t79f.

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

MLA Handbook (7th Edition):

Zhang, Yafeng. “Clustering and Registration of Functional Data with Applications in Time Course Genomics Data.” 2014. Web. 28 Nov 2020.

Vancouver:

Zhang Y. Clustering and Registration of Functional Data with Applications in Time Course Genomics Data. [Internet] [Thesis]. UCLA; 2014. [cited 2020 Nov 28]. Available from: http://www.escholarship.org/uc/item/0d01t79f.

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

Council of Science Editors:

Zhang Y. Clustering and Registration of Functional Data with Applications in Time Course Genomics Data. [Thesis]. UCLA; 2014. Available from: http://www.escholarship.org/uc/item/0d01t79f

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


University of Waterloo

8. Tian, Renfang. On Functional Data Analysis: Methodologies and Applications.

Degree: 2020, University of Waterloo

 In economic analyses, the variables of interest are often functions defined on continua such as time or space, though we may only have access to… (more)

Subjects/Keywords: Econometrics; Functional data analysis; Functional dynamic factor model; Functional regression; Simulation study; Theory and application

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APA (6th Edition):

Tian, R. (2020). On Functional Data Analysis: Methodologies and Applications. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/15811

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):

Tian, Renfang. “On Functional Data Analysis: Methodologies and Applications.” 2020. Thesis, University of Waterloo. Accessed November 28, 2020. http://hdl.handle.net/10012/15811.

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

MLA Handbook (7th Edition):

Tian, Renfang. “On Functional Data Analysis: Methodologies and Applications.” 2020. Web. 28 Nov 2020.

Vancouver:

Tian R. On Functional Data Analysis: Methodologies and Applications. [Internet] [Thesis]. University of Waterloo; 2020. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/10012/15811.

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

Council of Science Editors:

Tian R. On Functional Data Analysis: Methodologies and Applications. [Thesis]. University of Waterloo; 2020. Available from: http://hdl.handle.net/10012/15811

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


UCLA

9. Scheffler, Aaron Wolfe. Modeling Region-Referenced Longitudinal Functional Electroencephalography Data.

Degree: Biostatistics, 2019, UCLA

 Highly structured data collected in a variety of biomedical applications such as electroencephalography (EEG) are discrete samples of a smooth functional process observed across both… (more)

Subjects/Keywords: Biostatistics; Autism; Electroencephalography; Functional data analysis; Functional principal components analysis; Functional regression; Penalized regression

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APA (6th Edition):

Scheffler, A. W. (2019). Modeling Region-Referenced Longitudinal Functional Electroencephalography Data. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/60m6q662

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):

Scheffler, Aaron Wolfe. “Modeling Region-Referenced Longitudinal Functional Electroencephalography Data.” 2019. Thesis, UCLA. Accessed November 28, 2020. http://www.escholarship.org/uc/item/60m6q662.

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

MLA Handbook (7th Edition):

Scheffler, Aaron Wolfe. “Modeling Region-Referenced Longitudinal Functional Electroencephalography Data.” 2019. Web. 28 Nov 2020.

Vancouver:

Scheffler AW. Modeling Region-Referenced Longitudinal Functional Electroencephalography Data. [Internet] [Thesis]. UCLA; 2019. [cited 2020 Nov 28]. Available from: http://www.escholarship.org/uc/item/60m6q662.

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

Council of Science Editors:

Scheffler AW. Modeling Region-Referenced Longitudinal Functional Electroencephalography Data. [Thesis]. UCLA; 2019. Available from: http://www.escholarship.org/uc/item/60m6q662

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


Boston University

10. Liu, Chong. Functional principal component and factor analysis of spatially correlated data.

Degree: PhD, Mathematics & Statistics, 2014, Boston University

 While multivariate data analysis is concerned with data in the form of random vectors, functional data analysis goes one big step farther, focusing on data(more)

Subjects/Keywords: Statistics; Functional data analysis; Functional factor rotation; Functional principal component; Spatial correlation

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APA (6th Edition):

Liu, C. (2014). Functional principal component and factor analysis of spatially correlated data. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/14305

Chicago Manual of Style (16th Edition):

Liu, Chong. “Functional principal component and factor analysis of spatially correlated data.” 2014. Doctoral Dissertation, Boston University. Accessed November 28, 2020. http://hdl.handle.net/2144/14305.

MLA Handbook (7th Edition):

Liu, Chong. “Functional principal component and factor analysis of spatially correlated data.” 2014. Web. 28 Nov 2020.

Vancouver:

Liu C. Functional principal component and factor analysis of spatially correlated data. [Internet] [Doctoral dissertation]. Boston University; 2014. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/2144/14305.

Council of Science Editors:

Liu C. Functional principal component and factor analysis of spatially correlated data. [Doctoral Dissertation]. Boston University; 2014. Available from: http://hdl.handle.net/2144/14305


Cornell University

11. Soiaporn, Kunlaya. On The Modeling Of Multiple Functional Outcomes With Spatially Heterogeneous Shape Characteristics.

Degree: PhD, Operations Research, 2014, Cornell University

 This dissertation presents an approach for analyzing functional data with multiple outcomes that exhibits spatially heterogeneous shape characteristics. An example of data of this type… (more)

Subjects/Keywords: correlated functional outcomes; diffusion tensor imaging; skewed functional data

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APA (6th Edition):

Soiaporn, K. (2014). On The Modeling Of Multiple Functional Outcomes With Spatially Heterogeneous Shape Characteristics. (Doctoral Dissertation). Cornell University. Retrieved from http://hdl.handle.net/1813/36106

Chicago Manual of Style (16th Edition):

Soiaporn, Kunlaya. “On The Modeling Of Multiple Functional Outcomes With Spatially Heterogeneous Shape Characteristics.” 2014. Doctoral Dissertation, Cornell University. Accessed November 28, 2020. http://hdl.handle.net/1813/36106.

MLA Handbook (7th Edition):

Soiaporn, Kunlaya. “On The Modeling Of Multiple Functional Outcomes With Spatially Heterogeneous Shape Characteristics.” 2014. Web. 28 Nov 2020.

Vancouver:

Soiaporn K. On The Modeling Of Multiple Functional Outcomes With Spatially Heterogeneous Shape Characteristics. [Internet] [Doctoral dissertation]. Cornell University; 2014. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1813/36106.

Council of Science Editors:

Soiaporn K. On The Modeling Of Multiple Functional Outcomes With Spatially Heterogeneous Shape Characteristics. [Doctoral Dissertation]. Cornell University; 2014. Available from: http://hdl.handle.net/1813/36106


University of Georgia

12. Ettinger, Bree. Bivariate splines for ozone concentration predictions.

Degree: 2014, University of Georgia

 For ground level ozone prediction, we consider a functional linear regression model where the explanatory variable is a real random surface and the response is… (more)

Subjects/Keywords: Functional Linear Models; Functional Data; Regression; Splines; Principle Component Analysis

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APA (6th Edition):

Ettinger, B. (2014). Bivariate splines for ozone concentration predictions. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/25790

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):

Ettinger, Bree. “Bivariate splines for ozone concentration predictions.” 2014. Thesis, University of Georgia. Accessed November 28, 2020. http://hdl.handle.net/10724/25790.

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

MLA Handbook (7th Edition):

Ettinger, Bree. “Bivariate splines for ozone concentration predictions.” 2014. Web. 28 Nov 2020.

Vancouver:

Ettinger B. Bivariate splines for ozone concentration predictions. [Internet] [Thesis]. University of Georgia; 2014. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/10724/25790.

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

Council of Science Editors:

Ettinger B. Bivariate splines for ozone concentration predictions. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/25790

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


Penn State University

13. Constantinou, Panayiotis. TESTING SEPARABILITY OF FUNCTIONAL DATA.

Degree: 2017, Penn State University

 The assumption of separability is used heavily in spatiotemporal statistics. Separability means that the spatiotemporal covariance structure factors into the product of two functions, one… (more)

Subjects/Keywords: Separability; Functional data; Space-time processes; Functional panels

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APA (6th Edition):

Constantinou, P. (2017). TESTING SEPARABILITY OF FUNCTIONAL DATA. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/14253pzc140

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):

Constantinou, Panayiotis. “TESTING SEPARABILITY OF FUNCTIONAL DATA.” 2017. Thesis, Penn State University. Accessed November 28, 2020. https://submit-etda.libraries.psu.edu/catalog/14253pzc140.

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

MLA Handbook (7th Edition):

Constantinou, Panayiotis. “TESTING SEPARABILITY OF FUNCTIONAL DATA.” 2017. Web. 28 Nov 2020.

Vancouver:

Constantinou P. TESTING SEPARABILITY OF FUNCTIONAL DATA. [Internet] [Thesis]. Penn State University; 2017. [cited 2020 Nov 28]. Available from: https://submit-etda.libraries.psu.edu/catalog/14253pzc140.

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

Council of Science Editors:

Constantinou P. TESTING SEPARABILITY OF FUNCTIONAL DATA. [Thesis]. Penn State University; 2017. Available from: https://submit-etda.libraries.psu.edu/catalog/14253pzc140

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


University of Toronto

14. Lei, Edwin Kam Fai. Methods for Sparse Functional Data.

Degree: PhD, 2014, University of Toronto

 The primary aim of this thesis is to study methods for the analysis of sparse functional data. Since this type of data is observed infrequently… (more)

Subjects/Keywords: Dimension reduction; Functional principal components; Smoothing; Sparse functional data; 0463

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APA (6th Edition):

Lei, E. K. F. (2014). Methods for Sparse Functional Data. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/68427

Chicago Manual of Style (16th Edition):

Lei, Edwin Kam Fai. “Methods for Sparse Functional Data.” 2014. Doctoral Dissertation, University of Toronto. Accessed November 28, 2020. http://hdl.handle.net/1807/68427.

MLA Handbook (7th Edition):

Lei, Edwin Kam Fai. “Methods for Sparse Functional Data.” 2014. Web. 28 Nov 2020.

Vancouver:

Lei EKF. Methods for Sparse Functional Data. [Internet] [Doctoral dissertation]. University of Toronto; 2014. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1807/68427.

Council of Science Editors:

Lei EKF. Methods for Sparse Functional Data. [Doctoral Dissertation]. University of Toronto; 2014. Available from: http://hdl.handle.net/1807/68427


Kansas State University

15. Wu, Mengjiao. Equivalence testing for identity authentication using pulse waves from photoplethysmograph.

Degree: PhD, Department of Statistics, 2019, Kansas State University

 Photoplethysmograph sensors use a light-based technology to sense the rate of blood flow as controlled by the heart’s pumping action. This allows for a graphical… (more)

Subjects/Keywords: functional data; functional boxplots; permutation test; bootstrapping; equivalence testing

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APA (6th Edition):

Wu, M. (2019). Equivalence testing for identity authentication using pulse waves from photoplethysmograph. (Doctoral Dissertation). Kansas State University. Retrieved from http://hdl.handle.net/2097/39461

Chicago Manual of Style (16th Edition):

Wu, Mengjiao. “Equivalence testing for identity authentication using pulse waves from photoplethysmograph.” 2019. Doctoral Dissertation, Kansas State University. Accessed November 28, 2020. http://hdl.handle.net/2097/39461.

MLA Handbook (7th Edition):

Wu, Mengjiao. “Equivalence testing for identity authentication using pulse waves from photoplethysmograph.” 2019. Web. 28 Nov 2020.

Vancouver:

Wu M. Equivalence testing for identity authentication using pulse waves from photoplethysmograph. [Internet] [Doctoral dissertation]. Kansas State University; 2019. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/2097/39461.

Council of Science Editors:

Wu M. Equivalence testing for identity authentication using pulse waves from photoplethysmograph. [Doctoral Dissertation]. Kansas State University; 2019. Available from: http://hdl.handle.net/2097/39461


University of Alberta

16. Yaraee, Kate. Functional data analysis with application to MS and cervical vertebrae data.

Degree: MS, Department of Mathematical and Statistical Sciences, 2011, University of Alberta

Functional data analysis (FDA) is a fast-growing area in statistics with the aim of estimating a set of related functions or curves rather than focusing… (more)

Subjects/Keywords: Functional data analysis; Cervical Vertebrae; Multiple Sclerosis

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APA (6th Edition):

Yaraee, K. (2011). Functional data analysis with application to MS and cervical vertebrae data. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/s1784m780

Chicago Manual of Style (16th Edition):

Yaraee, Kate. “Functional data analysis with application to MS and cervical vertebrae data.” 2011. Masters Thesis, University of Alberta. Accessed November 28, 2020. https://era.library.ualberta.ca/files/s1784m780.

MLA Handbook (7th Edition):

Yaraee, Kate. “Functional data analysis with application to MS and cervical vertebrae data.” 2011. Web. 28 Nov 2020.

Vancouver:

Yaraee K. Functional data analysis with application to MS and cervical vertebrae data. [Internet] [Masters thesis]. University of Alberta; 2011. [cited 2020 Nov 28]. Available from: https://era.library.ualberta.ca/files/s1784m780.

Council of Science Editors:

Yaraee K. Functional data analysis with application to MS and cervical vertebrae data. [Masters Thesis]. University of Alberta; 2011. Available from: https://era.library.ualberta.ca/files/s1784m780


Texas A&M University

17. He, Shiyuan. Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination.

Degree: PhD, Statistics, 2017, Texas A&M University

 Both type Ia supernovae and variable stars are important distance indicators in astronomy. The peak luminosity of type Ia supernovae and the period-luminosity relation of… (more)

Subjects/Keywords: functional data; type Ia supernova; Mira variable

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

APA (6th Edition):

He, S. (2017). Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/161496

Chicago Manual of Style (16th Edition):

He, Shiyuan. “Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination.” 2017. Doctoral Dissertation, Texas A&M University. Accessed November 28, 2020. http://hdl.handle.net/1969.1/161496.

MLA Handbook (7th Edition):

He, Shiyuan. “Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination.” 2017. Web. 28 Nov 2020.

Vancouver:

He S. Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination. [Internet] [Doctoral dissertation]. Texas A&M University; 2017. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1969.1/161496.

Council of Science Editors:

He S. Functional Light Curve Models for Type Ia Supernovae and Mira Variables, with Their Application of Distance Determination. [Doctoral Dissertation]. Texas A&M University; 2017. Available from: http://hdl.handle.net/1969.1/161496


University of Vermont

18. King, Katherine S. Functional Data Analysis With Application to United States Weather Data.

Degree: Mathematics and Statistics, 2014, University of Vermont

  This thesis explores the use of functional data analytic methods to examine climate change in a select group of 16 cities in the United… (more)

Subjects/Keywords: Functional Data Analysis; Weather; Statistics; Splines

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

APA (6th Edition):

King, K. S. (2014). Functional Data Analysis With Application to United States Weather Data. (Thesis). University of Vermont. Retrieved from https://scholarworks.uvm.edu/hcoltheses/10

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):

King, Katherine S. “Functional Data Analysis With Application to United States Weather Data.” 2014. Thesis, University of Vermont. Accessed November 28, 2020. https://scholarworks.uvm.edu/hcoltheses/10.

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

MLA Handbook (7th Edition):

King, Katherine S. “Functional Data Analysis With Application to United States Weather Data.” 2014. Web. 28 Nov 2020.

Vancouver:

King KS. Functional Data Analysis With Application to United States Weather Data. [Internet] [Thesis]. University of Vermont; 2014. [cited 2020 Nov 28]. Available from: https://scholarworks.uvm.edu/hcoltheses/10.

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

Council of Science Editors:

King KS. Functional Data Analysis With Application to United States Weather Data. [Thesis]. University of Vermont; 2014. Available from: https://scholarworks.uvm.edu/hcoltheses/10

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


Texas Tech University

19. Kaphle, Krishna. Perturbations of Operators with Application to Testing Equality of Covariance Operators.

Degree: Mathematics and Statistics, 2011, Texas Tech University

 The generalization of multivariate statistical procedures to infinite dimension naturally requires extra theoretical work. In this dissertation, we will focus on testing the equality of… (more)

Subjects/Keywords: Covariance operators; Functional data; Delta method

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APA (6th Edition):

Kaphle, K. (2011). Perturbations of Operators with Application to Testing Equality of Covariance Operators. (Thesis). Texas Tech University. Retrieved from http://hdl.handle.net/2346/ETD-TTU-2011-08-1601

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):

Kaphle, Krishna. “Perturbations of Operators with Application to Testing Equality of Covariance Operators.” 2011. Thesis, Texas Tech University. Accessed November 28, 2020. http://hdl.handle.net/2346/ETD-TTU-2011-08-1601.

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

MLA Handbook (7th Edition):

Kaphle, Krishna. “Perturbations of Operators with Application to Testing Equality of Covariance Operators.” 2011. Web. 28 Nov 2020.

Vancouver:

Kaphle K. Perturbations of Operators with Application to Testing Equality of Covariance Operators. [Internet] [Thesis]. Texas Tech University; 2011. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/2346/ETD-TTU-2011-08-1601.

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

Council of Science Editors:

Kaphle K. Perturbations of Operators with Application to Testing Equality of Covariance Operators. [Thesis]. Texas Tech University; 2011. Available from: http://hdl.handle.net/2346/ETD-TTU-2011-08-1601

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


University of Limerick

20. O'Shea, Pádraig. B-spline smoothing and statistical inference for systems of differential equations.

Degree: 2019, University of Limerick

peer-reviewed

Traditional algorithms for modelling functional data use derivative-based optimisation methods to fit parameters. The process of finnding the derivatives of the fitting criterion with… (more)

Subjects/Keywords: algorithms; functional data analysis; FDA problems

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APA (6th Edition):

O'Shea, P. (2019). B-spline smoothing and statistical inference for systems of differential equations. (Thesis). University of Limerick. Retrieved from http://hdl.handle.net/10344/8496

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):

O'Shea, Pádraig. “B-spline smoothing and statistical inference for systems of differential equations.” 2019. Thesis, University of Limerick. Accessed November 28, 2020. http://hdl.handle.net/10344/8496.

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

MLA Handbook (7th Edition):

O'Shea, Pádraig. “B-spline smoothing and statistical inference for systems of differential equations.” 2019. Web. 28 Nov 2020.

Vancouver:

O'Shea P. B-spline smoothing and statistical inference for systems of differential equations. [Internet] [Thesis]. University of Limerick; 2019. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/10344/8496.

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

Council of Science Editors:

O'Shea P. B-spline smoothing and statistical inference for systems of differential equations. [Thesis]. University of Limerick; 2019. Available from: http://hdl.handle.net/10344/8496

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


Arizona State University

21. Ward, Kimberly. Handling Sparse and Missing Data in Functional Data Analysis: A Functional Mixed-Effects Model Approach.

Degree: Psychology, 2016, Arizona State University

 This paper investigates a relatively new analysis method for longitudinal data in the framework of functional data analysis. This approach treats longitudinal data as so-called… (more)

Subjects/Keywords: Psychology; Functional Data Analysis; Longitudinal Data; Mixed Models

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

APA (6th Edition):

Ward, K. (2016). Handling Sparse and Missing Data in Functional Data Analysis: A Functional Mixed-Effects Model Approach. (Masters Thesis). Arizona State University. Retrieved from http://repository.asu.edu/items/40749

Chicago Manual of Style (16th Edition):

Ward, Kimberly. “Handling Sparse and Missing Data in Functional Data Analysis: A Functional Mixed-Effects Model Approach.” 2016. Masters Thesis, Arizona State University. Accessed November 28, 2020. http://repository.asu.edu/items/40749.

MLA Handbook (7th Edition):

Ward, Kimberly. “Handling Sparse and Missing Data in Functional Data Analysis: A Functional Mixed-Effects Model Approach.” 2016. Web. 28 Nov 2020.

Vancouver:

Ward K. Handling Sparse and Missing Data in Functional Data Analysis: A Functional Mixed-Effects Model Approach. [Internet] [Masters thesis]. Arizona State University; 2016. [cited 2020 Nov 28]. Available from: http://repository.asu.edu/items/40749.

Council of Science Editors:

Ward K. Handling Sparse and Missing Data in Functional Data Analysis: A Functional Mixed-Effects Model Approach. [Masters Thesis]. Arizona State University; 2016. Available from: http://repository.asu.edu/items/40749


Princeton University

22. Zhu, Qian. Detecting gene similarities using large-scale content-based search systems .

Degree: PhD, 2016, Princeton University

 The accumulation of public gene expression datasets offers numerous opportunities for researchers to utilize these data to characterize gene functions, understand pathway actions, and formulate… (more)

Subjects/Keywords: big data; coexpression; data integration; functional genomics; gene expression; meta-analysis

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APA (6th Edition):

Zhu, Q. (2016). Detecting gene similarities using large-scale content-based search systems . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp016h440v94d

Chicago Manual of Style (16th Edition):

Zhu, Qian. “Detecting gene similarities using large-scale content-based search systems .” 2016. Doctoral Dissertation, Princeton University. Accessed November 28, 2020. http://arks.princeton.edu/ark:/88435/dsp016h440v94d.

MLA Handbook (7th Edition):

Zhu, Qian. “Detecting gene similarities using large-scale content-based search systems .” 2016. Web. 28 Nov 2020.

Vancouver:

Zhu Q. Detecting gene similarities using large-scale content-based search systems . [Internet] [Doctoral dissertation]. Princeton University; 2016. [cited 2020 Nov 28]. Available from: http://arks.princeton.edu/ark:/88435/dsp016h440v94d.

Council of Science Editors:

Zhu Q. Detecting gene similarities using large-scale content-based search systems . [Doctoral Dissertation]. Princeton University; 2016. Available from: http://arks.princeton.edu/ark:/88435/dsp016h440v94d

23. Shou, Haochang. Statistical Methods for Structured Multilevel Functional Data: Estimation and Reliability.

Degree: 2014, Johns Hopkins University

 The thesis investigates a specific type of functional data with multilevel structures induced by complex experimental designs. Novel statistical methods based on principal component analysis… (more)

Subjects/Keywords: functional data analysis; multilevel and structured data; high-dimensional data; imaging reproducibility; shrinkage estimation

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APA (6th Edition):

Shou, H. (2014). Statistical Methods for Structured Multilevel Functional Data: Estimation and Reliability. (Thesis). Johns Hopkins University. Retrieved from http://jhir.library.jhu.edu/handle/1774.2/37867

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):

Shou, Haochang. “Statistical Methods for Structured Multilevel Functional Data: Estimation and Reliability.” 2014. Thesis, Johns Hopkins University. Accessed November 28, 2020. http://jhir.library.jhu.edu/handle/1774.2/37867.

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

MLA Handbook (7th Edition):

Shou, Haochang. “Statistical Methods for Structured Multilevel Functional Data: Estimation and Reliability.” 2014. Web. 28 Nov 2020.

Vancouver:

Shou H. Statistical Methods for Structured Multilevel Functional Data: Estimation and Reliability. [Internet] [Thesis]. Johns Hopkins University; 2014. [cited 2020 Nov 28]. Available from: http://jhir.library.jhu.edu/handle/1774.2/37867.

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

Council of Science Editors:

Shou H. Statistical Methods for Structured Multilevel Functional Data: Estimation and Reliability. [Thesis]. Johns Hopkins University; 2014. Available from: http://jhir.library.jhu.edu/handle/1774.2/37867

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


Queen Mary, University of London

24. Zhang, Bairu. Functional data analysis in orthogonal designs with applications to gait patterns.

Degree: PhD, 2018, Queen Mary, University of London

 This thesis presents a contribution to the active research area of functional data analysis (FDA) and is concerned with the analysis of data from complex… (more)

Subjects/Keywords: Mathematical Sciences; Gait Patterns; functional data analysis; functional analysis of variance; ANOVA

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

APA (6th Edition):

Zhang, B. (2018). Functional data analysis in orthogonal designs with applications to gait patterns. (Doctoral Dissertation). Queen Mary, University of London. Retrieved from http://qmro.qmul.ac.uk/xmlui/handle/123456789/44698 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.766224

Chicago Manual of Style (16th Edition):

Zhang, Bairu. “Functional data analysis in orthogonal designs with applications to gait patterns.” 2018. Doctoral Dissertation, Queen Mary, University of London. Accessed November 28, 2020. http://qmro.qmul.ac.uk/xmlui/handle/123456789/44698 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.766224.

MLA Handbook (7th Edition):

Zhang, Bairu. “Functional data analysis in orthogonal designs with applications to gait patterns.” 2018. Web. 28 Nov 2020.

Vancouver:

Zhang B. Functional data analysis in orthogonal designs with applications to gait patterns. [Internet] [Doctoral dissertation]. Queen Mary, University of London; 2018. [cited 2020 Nov 28]. Available from: http://qmro.qmul.ac.uk/xmlui/handle/123456789/44698 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.766224.

Council of Science Editors:

Zhang B. Functional data analysis in orthogonal designs with applications to gait patterns. [Doctoral Dissertation]. Queen Mary, University of London; 2018. Available from: http://qmro.qmul.ac.uk/xmlui/handle/123456789/44698 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.766224


University of Toronto

25. Lin, Zhenhua. Adaptive Functional Data Analysis.

Degree: PhD, 2017, University of Toronto

 Statistical methods that adapt to individual observations or unknown population structures are attractive due to both numerical and theoretical advantages over their non-adaptive counterparts. In… (more)

Subjects/Keywords: Contaminated functional data; Functional data analysis; Infinite mixture; local linear manifold smoothing; Phase transition; Trajectory representation; 0463

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

APA (6th Edition):

Lin, Z. (2017). Adaptive Functional Data Analysis. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/80668

Chicago Manual of Style (16th Edition):

Lin, Zhenhua. “Adaptive Functional Data Analysis.” 2017. Doctoral Dissertation, University of Toronto. Accessed November 28, 2020. http://hdl.handle.net/1807/80668.

MLA Handbook (7th Edition):

Lin, Zhenhua. “Adaptive Functional Data Analysis.” 2017. Web. 28 Nov 2020.

Vancouver:

Lin Z. Adaptive Functional Data Analysis. [Internet] [Doctoral dissertation]. University of Toronto; 2017. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1807/80668.

Council of Science Editors:

Lin Z. Adaptive Functional Data Analysis. [Doctoral Dissertation]. University of Toronto; 2017. Available from: http://hdl.handle.net/1807/80668


Utah State University

26. Zhang, Xi. Empirical Properties of Functional Regression Models and Application to High-Frequency Financial Data.

Degree: PhD, Mathematics and Statistics, 2013, Utah State University

Functional data analysis (FDA) has grown into a substantial field of statistical research, with new methodology, numerous useful applications and interesting novel theoretical developments. My… (more)

Subjects/Keywords: Empirical Study; Financial Data; Functional Data Analysis; Functional Regression Models; Finance and Financial Management; Statistics and Probability

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APA (6th Edition):

Zhang, X. (2013). Empirical Properties of Functional Regression Models and Application to High-Frequency Financial Data. (Doctoral Dissertation). Utah State University. Retrieved from https://digitalcommons.usu.edu/etd/1973

Chicago Manual of Style (16th Edition):

Zhang, Xi. “Empirical Properties of Functional Regression Models and Application to High-Frequency Financial Data.” 2013. Doctoral Dissertation, Utah State University. Accessed November 28, 2020. https://digitalcommons.usu.edu/etd/1973.

MLA Handbook (7th Edition):

Zhang, Xi. “Empirical Properties of Functional Regression Models and Application to High-Frequency Financial Data.” 2013. Web. 28 Nov 2020.

Vancouver:

Zhang X. Empirical Properties of Functional Regression Models and Application to High-Frequency Financial Data. [Internet] [Doctoral dissertation]. Utah State University; 2013. [cited 2020 Nov 28]. Available from: https://digitalcommons.usu.edu/etd/1973.

Council of Science Editors:

Zhang X. Empirical Properties of Functional Regression Models and Application to High-Frequency Financial Data. [Doctoral Dissertation]. Utah State University; 2013. Available from: https://digitalcommons.usu.edu/etd/1973


McMaster University

27. Cheam, Amay SM. Mixture models for ROC curve and spatio-temporal clustering.

Degree: PhD, 2016, McMaster University

Finite mixture models have had a profound impact on the history of statistics, contributing to modelling heterogeneous populations, generalizing distributional assumptions, and lately, presenting a… (more)

Subjects/Keywords: Finite mixture models; ROC curve; Spatio-temporal data; Functional data; Model-based clustering; EM algorithm

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APA (6th Edition):

Cheam, A. S. (2016). Mixture models for ROC curve and spatio-temporal clustering. (Doctoral Dissertation). McMaster University. Retrieved from http://hdl.handle.net/11375/20693

Chicago Manual of Style (16th Edition):

Cheam, Amay SM. “Mixture models for ROC curve and spatio-temporal clustering.” 2016. Doctoral Dissertation, McMaster University. Accessed November 28, 2020. http://hdl.handle.net/11375/20693.

MLA Handbook (7th Edition):

Cheam, Amay SM. “Mixture models for ROC curve and spatio-temporal clustering.” 2016. Web. 28 Nov 2020.

Vancouver:

Cheam AS. Mixture models for ROC curve and spatio-temporal clustering. [Internet] [Doctoral dissertation]. McMaster University; 2016. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/11375/20693.

Council of Science Editors:

Cheam AS. Mixture models for ROC curve and spatio-temporal clustering. [Doctoral Dissertation]. McMaster University; 2016. Available from: http://hdl.handle.net/11375/20693


New Jersey Institute of Technology

28. Kamble, Amit Madhukar. Motor data scaling by respiration frequencies in rest.

Degree: MSin Biomedical Engineering - (M.S.), Biomedical Engineering, 2010, New Jersey Institute of Technology

Functional Magnetic Resonance Imaging (fMRI) is widely used as a tool to see activations in the different brain regions. Motor data acquired from fMRI… (more)

Subjects/Keywords: Functional magnetic resonance imaging; Motor data; Respiration frequencies; Scaling data; Biomedical Engineering and Bioengineering

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APA (6th Edition):

Kamble, A. M. (2010). Motor data scaling by respiration frequencies in rest. (Thesis). New Jersey Institute of Technology. Retrieved from https://digitalcommons.njit.edu/theses/76

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):

Kamble, Amit Madhukar. “Motor data scaling by respiration frequencies in rest.” 2010. Thesis, New Jersey Institute of Technology. Accessed November 28, 2020. https://digitalcommons.njit.edu/theses/76.

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

MLA Handbook (7th Edition):

Kamble, Amit Madhukar. “Motor data scaling by respiration frequencies in rest.” 2010. Web. 28 Nov 2020.

Vancouver:

Kamble AM. Motor data scaling by respiration frequencies in rest. [Internet] [Thesis]. New Jersey Institute of Technology; 2010. [cited 2020 Nov 28]. Available from: https://digitalcommons.njit.edu/theses/76.

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

Council of Science Editors:

Kamble AM. Motor data scaling by respiration frequencies in rest. [Thesis]. New Jersey Institute of Technology; 2010. Available from: https://digitalcommons.njit.edu/theses/76

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

29. Lai, Chinh Thi Tuyet. Respiratory disease diagnosis for dolphin using breath data .

Degree: 2017, Texas A&M University – Corpus Christi

 Respiratory disease in marine mammals evokes strong public attention as well as worthwhile scientific interest. Traditional methods for animal disease diagnosis include blood test, ultrasound,… (more)

Subjects/Keywords: breath data; dolphin; functional data analysis; geometric models; respiratory disease diagnosis; principal component analysis

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APA (6th Edition):

Lai, C. T. T. (2017). Respiratory disease diagnosis for dolphin using breath data . (Thesis). Texas A&M University – Corpus Christi. Retrieved from http://hdl.handle.net/1969.6/19202

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):

Lai, Chinh Thi Tuyet. “Respiratory disease diagnosis for dolphin using breath data .” 2017. Thesis, Texas A&M University – Corpus Christi. Accessed November 28, 2020. http://hdl.handle.net/1969.6/19202.

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

MLA Handbook (7th Edition):

Lai, Chinh Thi Tuyet. “Respiratory disease diagnosis for dolphin using breath data .” 2017. Web. 28 Nov 2020.

Vancouver:

Lai CTT. Respiratory disease diagnosis for dolphin using breath data . [Internet] [Thesis]. Texas A&M University – Corpus Christi; 2017. [cited 2020 Nov 28]. Available from: http://hdl.handle.net/1969.6/19202.

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

Council of Science Editors:

Lai CTT. Respiratory disease diagnosis for dolphin using breath data . [Thesis]. Texas A&M University – Corpus Christi; 2017. Available from: http://hdl.handle.net/1969.6/19202

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


University of Cambridge

30. Lila, Eardi. Geometric Functional Data Analysis.

Degree: PhD, 2019, University of Cambridge

 In this thesis, we introduce a comprehensive framework for the analysis of statistical samples that are functional data with non-trivial geometry. Geometry can interplay with… (more)

Subjects/Keywords: Functional Data Analysis; Manifold Data Analysis; Shape Analysis; Neuroimaging; Brain Connectivity; Inverse Problems

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

APA (6th Edition):

Lila, E. (2019). Geometric Functional Data Analysis. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/297866

Chicago Manual of Style (16th Edition):

Lila, Eardi. “Geometric Functional Data Analysis.” 2019. Doctoral Dissertation, University of Cambridge. Accessed November 28, 2020. https://www.repository.cam.ac.uk/handle/1810/297866.

MLA Handbook (7th Edition):

Lila, Eardi. “Geometric Functional Data Analysis.” 2019. Web. 28 Nov 2020.

Vancouver:

Lila E. Geometric Functional Data Analysis. [Internet] [Doctoral dissertation]. University of Cambridge; 2019. [cited 2020 Nov 28]. Available from: https://www.repository.cam.ac.uk/handle/1810/297866.

Council of Science Editors:

Lila E. Geometric Functional Data Analysis. [Doctoral Dissertation]. University of Cambridge; 2019. Available from: https://www.repository.cam.ac.uk/handle/1810/297866

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