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You searched for subject:(shrinkage regression). Showing records 1 – 19 of 19 total matches.

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Mississippi State University

1. Phillips, Katie Lynn. An application of ridge regression and LASSO methods for model selection.

Degree: MS, Mathematics and Statistics, 2018, Mississippi State University

 Ordinary Least Squares (OLS) models are popular tools among field scientists, because they are easy to understand and use. Although OLS estimators are unbiased, it… (more)

Subjects/Keywords: shrinkage; LASSO; ridge regression

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APA (6th Edition):

Phillips, K. L. (2018). An application of ridge regression and LASSO methods for model selection. (Masters Thesis). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-06182018-094706/ ;

Chicago Manual of Style (16th Edition):

Phillips, Katie Lynn. “An application of ridge regression and LASSO methods for model selection.” 2018. Masters Thesis, Mississippi State University. Accessed June 25, 2019. http://sun.library.msstate.edu/ETD-db/theses/available/etd-06182018-094706/ ;.

MLA Handbook (7th Edition):

Phillips, Katie Lynn. “An application of ridge regression and LASSO methods for model selection.” 2018. Web. 25 Jun 2019.

Vancouver:

Phillips KL. An application of ridge regression and LASSO methods for model selection. [Internet] [Masters thesis]. Mississippi State University; 2018. [cited 2019 Jun 25]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06182018-094706/ ;.

Council of Science Editors:

Phillips KL. An application of ridge regression and LASSO methods for model selection. [Masters Thesis]. Mississippi State University; 2018. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-06182018-094706/ ;


University of Notre Dame

2. Charles Laurin. Lasso Meta-Regression and Its Application to Psychiatric Genomics</h1>.

Degree: PhD, Psychology, 2014, University of Notre Dame

  Meta-analysis is an essential technique in psychiatric genomics. Heterogeneity of the effect sizes included in a meta-analysis can reduce its statistical power. Meta-regression provides… (more)

Subjects/Keywords: meta-regression; meta-analysis; lasso; shrinkage regression

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APA (6th Edition):

Laurin, C. (2014). Lasso Meta-Regression and Its Application to Psychiatric Genomics</h1>. (Doctoral Dissertation). University of Notre Dame. Retrieved from https://curate.nd.edu/show/qj72p556n1d

Chicago Manual of Style (16th Edition):

Laurin, Charles. “Lasso Meta-Regression and Its Application to Psychiatric Genomics</h1>.” 2014. Doctoral Dissertation, University of Notre Dame. Accessed June 25, 2019. https://curate.nd.edu/show/qj72p556n1d.

MLA Handbook (7th Edition):

Laurin, Charles. “Lasso Meta-Regression and Its Application to Psychiatric Genomics</h1>.” 2014. Web. 25 Jun 2019.

Vancouver:

Laurin C. Lasso Meta-Regression and Its Application to Psychiatric Genomics</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2014. [cited 2019 Jun 25]. Available from: https://curate.nd.edu/show/qj72p556n1d.

Council of Science Editors:

Laurin C. Lasso Meta-Regression and Its Application to Psychiatric Genomics</h1>. [Doctoral Dissertation]. University of Notre Dame; 2014. Available from: https://curate.nd.edu/show/qj72p556n1d


University of Manitoba

3. Munaweera Arachchilage, Inesh Prabuddha. Shrinkage estimators under generalized garrote and LINEX loss functions for regression analysis.

Degree: Statistics, 2018, University of Manitoba

Shrinkage methods are widely used in multiple linear regression analysis to address the multicollinearity and some other issues in many practical situations. Most of the… (more)

Subjects/Keywords: LINEX regression; Multiple linear regression; Non-negative garrote; Shrinkage methods

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APA (6th Edition):

Munaweera Arachchilage, I. P. (2018). Shrinkage estimators under generalized garrote and LINEX loss functions for regression analysis. (Masters Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/33380

Chicago Manual of Style (16th Edition):

Munaweera Arachchilage, Inesh Prabuddha. “Shrinkage estimators under generalized garrote and LINEX loss functions for regression analysis.” 2018. Masters Thesis, University of Manitoba. Accessed June 25, 2019. http://hdl.handle.net/1993/33380.

MLA Handbook (7th Edition):

Munaweera Arachchilage, Inesh Prabuddha. “Shrinkage estimators under generalized garrote and LINEX loss functions for regression analysis.” 2018. Web. 25 Jun 2019.

Vancouver:

Munaweera Arachchilage IP. Shrinkage estimators under generalized garrote and LINEX loss functions for regression analysis. [Internet] [Masters thesis]. University of Manitoba; 2018. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/1993/33380.

Council of Science Editors:

Munaweera Arachchilage IP. Shrinkage estimators under generalized garrote and LINEX loss functions for regression analysis. [Masters Thesis]. University of Manitoba; 2018. Available from: http://hdl.handle.net/1993/33380


University of Victoria

4. Greenlaw, Keelin. A Bayesian Group Sparse Multi-Task Regression Model for Imaging Genomics.

Degree: Department of Mathematics and Statistics, 2015, University of Victoria

 Recent advances in technology for brain imaging and high-throughput genotyping have motivated studies examining the influence of genetic variation on brain structure. In this setting,… (more)

Subjects/Keywords: Bayesian Shrinkage; Imaging Genomics; Tuning Parameter Selection; Multivariate Regression

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APA (6th Edition):

Greenlaw, K. (2015). A Bayesian Group Sparse Multi-Task Regression Model for Imaging Genomics. (Masters Thesis). University of Victoria. Retrieved from http://hdl.handle.net/1828/6577

Chicago Manual of Style (16th Edition):

Greenlaw, Keelin. “A Bayesian Group Sparse Multi-Task Regression Model for Imaging Genomics.” 2015. Masters Thesis, University of Victoria. Accessed June 25, 2019. http://hdl.handle.net/1828/6577.

MLA Handbook (7th Edition):

Greenlaw, Keelin. “A Bayesian Group Sparse Multi-Task Regression Model for Imaging Genomics.” 2015. Web. 25 Jun 2019.

Vancouver:

Greenlaw K. A Bayesian Group Sparse Multi-Task Regression Model for Imaging Genomics. [Internet] [Masters thesis]. University of Victoria; 2015. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/1828/6577.

Council of Science Editors:

Greenlaw K. A Bayesian Group Sparse Multi-Task Regression Model for Imaging Genomics. [Masters Thesis]. University of Victoria; 2015. Available from: http://hdl.handle.net/1828/6577


University of Windsor

5. Chen, Fuqi. Optimal Inference Methods in Linear Models with Change-points.

Degree: PhD, Mathematics and Statistics, 2014, University of Windsor

  In this dissertation, we consider an estimation problem of the regression coefficients in both multiple regression model and multivariate multiple regression model with several… (more)

Subjects/Keywords: ADR; change-points; mixingale array; multivariate regression; shrinkage estimators; Stein-rule

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APA (6th Edition):

Chen, F. (2014). Optimal Inference Methods in Linear Models with Change-points. (Doctoral Dissertation). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/5163

Chicago Manual of Style (16th Edition):

Chen, Fuqi. “Optimal Inference Methods in Linear Models with Change-points.” 2014. Doctoral Dissertation, University of Windsor. Accessed June 25, 2019. https://scholar.uwindsor.ca/etd/5163.

MLA Handbook (7th Edition):

Chen, Fuqi. “Optimal Inference Methods in Linear Models with Change-points.” 2014. Web. 25 Jun 2019.

Vancouver:

Chen F. Optimal Inference Methods in Linear Models with Change-points. [Internet] [Doctoral dissertation]. University of Windsor; 2014. [cited 2019 Jun 25]. Available from: https://scholar.uwindsor.ca/etd/5163.

Council of Science Editors:

Chen F. Optimal Inference Methods in Linear Models with Change-points. [Doctoral Dissertation]. University of Windsor; 2014. Available from: https://scholar.uwindsor.ca/etd/5163


University of Hawaii – Manoa

6. Liang, Lu. Closeness of Factor Analysis and Principal Component Analysis in Semi-High-Dimensional Conditions.

Degree: 2017, University of Hawaii – Manoa

Ph.D. University of Hawaii at Manoa 2016.

Factor analysis (FA) and principal component analysis (PCA) are routinely employed in research in the social sciences. Guttman… (more)

Subjects/Keywords: High-dimensionality; Large p small N; Regularization; Ridge regression; Shrinkage; Fisher’s z-transformation; Canonical correlation

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APA (6th Edition):

Liang, L. (2017). Closeness of Factor Analysis and Principal Component Analysis in Semi-High-Dimensional Conditions. (Thesis). University of Hawaii – Manoa. Retrieved from http://hdl.handle.net/10125/51387

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):

Liang, Lu. “Closeness of Factor Analysis and Principal Component Analysis in Semi-High-Dimensional Conditions.” 2017. Thesis, University of Hawaii – Manoa. Accessed June 25, 2019. http://hdl.handle.net/10125/51387.

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

MLA Handbook (7th Edition):

Liang, Lu. “Closeness of Factor Analysis and Principal Component Analysis in Semi-High-Dimensional Conditions.” 2017. Web. 25 Jun 2019.

Vancouver:

Liang L. Closeness of Factor Analysis and Principal Component Analysis in Semi-High-Dimensional Conditions. [Internet] [Thesis]. University of Hawaii – Manoa; 2017. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/10125/51387.

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

Council of Science Editors:

Liang L. Closeness of Factor Analysis and Principal Component Analysis in Semi-High-Dimensional Conditions. [Thesis]. University of Hawaii – Manoa; 2017. Available from: http://hdl.handle.net/10125/51387

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


University of Washington

7. Griffin, Maryclare Carney. Model-Based Penalized Regression.

Degree: PhD, 2018, University of Washington

 This thesis contains three chapters that consider penalized regression from a model-based perspective, interpreting penalties as assumed prior distributions for unknown regression coefficients. In the… (more)

Subjects/Keywords: adaptive inference; empirical Bayes; method of moments; penalized regression; shrinkage priors; structured data; Statistics; Statistics

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APA (6th Edition):

Griffin, M. C. (2018). Model-Based Penalized Regression. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/43160

Chicago Manual of Style (16th Edition):

Griffin, Maryclare Carney. “Model-Based Penalized Regression.” 2018. Doctoral Dissertation, University of Washington. Accessed June 25, 2019. http://hdl.handle.net/1773/43160.

MLA Handbook (7th Edition):

Griffin, Maryclare Carney. “Model-Based Penalized Regression.” 2018. Web. 25 Jun 2019.

Vancouver:

Griffin MC. Model-Based Penalized Regression. [Internet] [Doctoral dissertation]. University of Washington; 2018. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/1773/43160.

Council of Science Editors:

Griffin MC. Model-Based Penalized Regression. [Doctoral Dissertation]. University of Washington; 2018. Available from: http://hdl.handle.net/1773/43160


University of Windsor

8. Chen, Fuqi. Optimal Inference Methods in Linear Models with Change-points.

Degree: PhD, Mathematics and Statistics, 2014, University of Windsor

  In this dissertation, we consider an estimation problem of the regression coefficients in both multiple regression model and multivariate multiple regression model with several… (more)

Subjects/Keywords: Pure sciences; Asymptotic distributional risk; Change-points; Mixingale array; Multivariate regression; Shrinkage estimators; Stein-rule

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

APA (6th Edition):

Chen, F. (2014). Optimal Inference Methods in Linear Models with Change-points. (Doctoral Dissertation). University of Windsor. Retrieved from https://scholar.uwindsor.ca/etd/5084

Chicago Manual of Style (16th Edition):

Chen, Fuqi. “Optimal Inference Methods in Linear Models with Change-points.” 2014. Doctoral Dissertation, University of Windsor. Accessed June 25, 2019. https://scholar.uwindsor.ca/etd/5084.

MLA Handbook (7th Edition):

Chen, Fuqi. “Optimal Inference Methods in Linear Models with Change-points.” 2014. Web. 25 Jun 2019.

Vancouver:

Chen F. Optimal Inference Methods in Linear Models with Change-points. [Internet] [Doctoral dissertation]. University of Windsor; 2014. [cited 2019 Jun 25]. Available from: https://scholar.uwindsor.ca/etd/5084.

Council of Science Editors:

Chen F. Optimal Inference Methods in Linear Models with Change-points. [Doctoral Dissertation]. University of Windsor; 2014. Available from: https://scholar.uwindsor.ca/etd/5084


University of South Florida

9. Chen, Wei. Analysis of Rheumatoid Arthritis Data using Logistic Regression and Penalized Approach.

Degree: 2015, University of South Florida

 In this paper, a rheumatoid arthritis (RA) medicine clinical dataset with an ordinal response is selected to study this new medicine. In the dataset, there… (more)

Subjects/Keywords: logistic regression; shrinkage method; rheumatoid arthritis clinical trial data; Statistics and Probability

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APA (6th Edition):

Chen, W. (2015). Analysis of Rheumatoid Arthritis Data using Logistic Regression and Penalized Approach. (Thesis). University of South Florida. Retrieved from https://scholarcommons.usf.edu/etd/5923

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):

Chen, Wei. “Analysis of Rheumatoid Arthritis Data using Logistic Regression and Penalized Approach.” 2015. Thesis, University of South Florida. Accessed June 25, 2019. https://scholarcommons.usf.edu/etd/5923.

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

MLA Handbook (7th Edition):

Chen, Wei. “Analysis of Rheumatoid Arthritis Data using Logistic Regression and Penalized Approach.” 2015. Web. 25 Jun 2019.

Vancouver:

Chen W. Analysis of Rheumatoid Arthritis Data using Logistic Regression and Penalized Approach. [Internet] [Thesis]. University of South Florida; 2015. [cited 2019 Jun 25]. Available from: https://scholarcommons.usf.edu/etd/5923.

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

Council of Science Editors:

Chen W. Analysis of Rheumatoid Arthritis Data using Logistic Regression and Penalized Approach. [Thesis]. University of South Florida; 2015. Available from: https://scholarcommons.usf.edu/etd/5923

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


University of Southern California

10. Zheng, Zemin. Feature selection in high-dimensional modeling with thresholded regression.

Degree: PhD, Applied Mathematics, 2015, University of Southern California

 This dissertation addresses two challenging problems with respect to feature selection in the high-dimensional setting, where the number of covariates can be larger than the… (more)

Subjects/Keywords: prediction and variable selection; high dimensionality; hard-thresholding; global optimality; thresholded regression; shrinkage effect; latent confounding factors; principal components; model selection

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APA (6th Edition):

Zheng, Z. (2015). Feature selection in high-dimensional modeling with thresholded regression. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/544029/rec/2785

Chicago Manual of Style (16th Edition):

Zheng, Zemin. “Feature selection in high-dimensional modeling with thresholded regression.” 2015. Doctoral Dissertation, University of Southern California. Accessed June 25, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/544029/rec/2785.

MLA Handbook (7th Edition):

Zheng, Zemin. “Feature selection in high-dimensional modeling with thresholded regression.” 2015. Web. 25 Jun 2019.

Vancouver:

Zheng Z. Feature selection in high-dimensional modeling with thresholded regression. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2019 Jun 25]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/544029/rec/2785.

Council of Science Editors:

Zheng Z. Feature selection in high-dimensional modeling with thresholded regression. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/544029/rec/2785


Washington State University

11. [No author]. Soil Carbon Determination Using Rapid, Inexpensive, Non-destructive Spectroscopic Techniques .

Degree: 2012, Washington State University

 New methods are required to rapidly and accurately measure soil C at field- and landscape-scales to improve local, regional, and global soil C stock and… (more)

Subjects/Keywords: Soil sciences; in situ; Laser-induced breakdown spectroscopy; regression shrinkage and variable selection; soil carbon; Visible-near infrared; diffuse reflectance spectroscopy

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APA (6th Edition):

author], [. (2012). Soil Carbon Determination Using Rapid, Inexpensive, Non-destructive Spectroscopic Techniques . (Thesis). Washington State University. Retrieved from http://hdl.handle.net/2376/4668

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):

author], [No. “Soil Carbon Determination Using Rapid, Inexpensive, Non-destructive Spectroscopic Techniques .” 2012. Thesis, Washington State University. Accessed June 25, 2019. http://hdl.handle.net/2376/4668.

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

MLA Handbook (7th Edition):

author], [No. “Soil Carbon Determination Using Rapid, Inexpensive, Non-destructive Spectroscopic Techniques .” 2012. Web. 25 Jun 2019.

Vancouver:

author] [. Soil Carbon Determination Using Rapid, Inexpensive, Non-destructive Spectroscopic Techniques . [Internet] [Thesis]. Washington State University; 2012. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/2376/4668.

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

Council of Science Editors:

author] [. Soil Carbon Determination Using Rapid, Inexpensive, Non-destructive Spectroscopic Techniques . [Thesis]. Washington State University; 2012. Available from: http://hdl.handle.net/2376/4668

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


Utah State University

12. Yin, Ping. Estimating R2 Shrinkage in Multiple Regression: A Comparison of Different Analytical Methods.

Degree: MS, Psychology, 1999, Utah State University

  This study investigated the effectiveness of various analytical methods used for estimating R2 shrinkage in multiple regression analysis. Two categories of analytical formulae were… (more)

Subjects/Keywords: Estimating; shrinkage; multiple regression; comparison; analytical methods; Psychology

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APA (6th Edition):

Yin, P. (1999). Estimating R2 Shrinkage in Multiple Regression: A Comparison of Different Analytical Methods. (Masters Thesis). Utah State University. Retrieved from https://digitalcommons.usu.edu/etd/6147

Chicago Manual of Style (16th Edition):

Yin, Ping. “Estimating R2 Shrinkage in Multiple Regression: A Comparison of Different Analytical Methods.” 1999. Masters Thesis, Utah State University. Accessed June 25, 2019. https://digitalcommons.usu.edu/etd/6147.

MLA Handbook (7th Edition):

Yin, Ping. “Estimating R2 Shrinkage in Multiple Regression: A Comparison of Different Analytical Methods.” 1999. Web. 25 Jun 2019.

Vancouver:

Yin P. Estimating R2 Shrinkage in Multiple Regression: A Comparison of Different Analytical Methods. [Internet] [Masters thesis]. Utah State University; 1999. [cited 2019 Jun 25]. Available from: https://digitalcommons.usu.edu/etd/6147.

Council of Science Editors:

Yin P. Estimating R2 Shrinkage in Multiple Regression: A Comparison of Different Analytical Methods. [Masters Thesis]. Utah State University; 1999. Available from: https://digitalcommons.usu.edu/etd/6147


University of Illinois – Urbana-Champaign

13. Gan, Lu. Variable screening and model selection in censored quantile regression via sparse penalties and stepwise refinement.

Degree: PhD, 0329, 2014, University of Illinois – Urbana-Champaign

 Many variable selection methods are available for linear regression but very little has been developed for quantile regression, especially for the censored problems. This study… (more)

Subjects/Keywords: Variable Screening; Censored Data; Quantile Regression; Least Absolute Selection and Shrinkage Operator (LASSO); Smoothly Clipped Absolute Deviation (SCAD); Portnoy; Peng and Huang; Stepwise Regression; Bidirectional; Backward; Left Censoring; Random Censoring

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APA (6th Edition):

Gan, L. (2014). Variable screening and model selection in censored quantile regression via sparse penalties and stepwise refinement. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/49692

Chicago Manual of Style (16th Edition):

Gan, Lu. “Variable screening and model selection in censored quantile regression via sparse penalties and stepwise refinement.” 2014. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed June 25, 2019. http://hdl.handle.net/2142/49692.

MLA Handbook (7th Edition):

Gan, Lu. “Variable screening and model selection in censored quantile regression via sparse penalties and stepwise refinement.” 2014. Web. 25 Jun 2019.

Vancouver:

Gan L. Variable screening and model selection in censored quantile regression via sparse penalties and stepwise refinement. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2014. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/2142/49692.

Council of Science Editors:

Gan L. Variable screening and model selection in censored quantile regression via sparse penalties and stepwise refinement. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/49692


Georgia State University

14. Luo, Shan. Advanced Statistical Methodologies in Determining the Observation Time to Discriminate Viruses Using FTIR.

Degree: MS, Mathematics and Statistics, 2009, Georgia State University

 Fourier transform infrared (FTIR) spectroscopy, one method of electromagnetic radiation for detecting specific cellular molecular structure, can be used to discriminate different types of cells.… (more)

Subjects/Keywords: Bootstrap method; K-fold Cross-Validation; Shrinkage; Sensitivity; Specificity; Inner-difference; Intra-difference; Wilcoxon Signed-Rank Test; Partial Least Square Regression; Area Under the ROC Curve; Mathematics

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APA (6th Edition):

Luo, S. (2009). Advanced Statistical Methodologies in Determining the Observation Time to Discriminate Viruses Using FTIR. (Thesis). Georgia State University. Retrieved from https://scholarworks.gsu.edu/math_theses/86

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):

Luo, Shan. “Advanced Statistical Methodologies in Determining the Observation Time to Discriminate Viruses Using FTIR.” 2009. Thesis, Georgia State University. Accessed June 25, 2019. https://scholarworks.gsu.edu/math_theses/86.

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

MLA Handbook (7th Edition):

Luo, Shan. “Advanced Statistical Methodologies in Determining the Observation Time to Discriminate Viruses Using FTIR.” 2009. Web. 25 Jun 2019.

Vancouver:

Luo S. Advanced Statistical Methodologies in Determining the Observation Time to Discriminate Viruses Using FTIR. [Internet] [Thesis]. Georgia State University; 2009. [cited 2019 Jun 25]. Available from: https://scholarworks.gsu.edu/math_theses/86.

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

Council of Science Editors:

Luo S. Advanced Statistical Methodologies in Determining the Observation Time to Discriminate Viruses Using FTIR. [Thesis]. Georgia State University; 2009. Available from: https://scholarworks.gsu.edu/math_theses/86

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


University of Florida

15. Haranki, Boris. Strength, Modulus of Elasticity, Creep and Shrinkage of Concrete Used in Florida.

Degree: M.E., Civil Engineering - Civil and Coastal Engineering, 2009, University of Florida

 Title: Strength, Modulus of Elasticity, Creep and Shrinkage of Concrete used in Florida. Name: Boris Haranki Phone: (352)870-5495 email: [email protected] Department: Civil Engineering Supervisory committee… (more)

Subjects/Keywords: Cements; Compressive strength; Construction aggregate; Granite; Modeling; Moduli of elasticity; Proportional limit; Regression analysis; Specimens; Tensile strength; concrete, creep, elasticity, florida, modulus, shrinkage, strength

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APA (6th Edition):

Haranki, B. (2009). Strength, Modulus of Elasticity, Creep and Shrinkage of Concrete Used in Florida. (Masters Thesis). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0024506

Chicago Manual of Style (16th Edition):

Haranki, Boris. “Strength, Modulus of Elasticity, Creep and Shrinkage of Concrete Used in Florida.” 2009. Masters Thesis, University of Florida. Accessed June 25, 2019. http://ufdc.ufl.edu/UFE0024506.

MLA Handbook (7th Edition):

Haranki, Boris. “Strength, Modulus of Elasticity, Creep and Shrinkage of Concrete Used in Florida.” 2009. Web. 25 Jun 2019.

Vancouver:

Haranki B. Strength, Modulus of Elasticity, Creep and Shrinkage of Concrete Used in Florida. [Internet] [Masters thesis]. University of Florida; 2009. [cited 2019 Jun 25]. Available from: http://ufdc.ufl.edu/UFE0024506.

Council of Science Editors:

Haranki B. Strength, Modulus of Elasticity, Creep and Shrinkage of Concrete Used in Florida. [Masters Thesis]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0024506

16. Condon, Erin. Varying Coefficients in Logistic Regression with Applications to Marketing Research.

Degree: PhD, 0329, 2012, University of Illinois – Urbana-Champaign

 In the marketing research world today, companies have access to massive amounts of data regarding the purchase behavior of consumers. Researchers study this data to… (more)

Subjects/Keywords: varying coefficients; group LASSO; marketing research; logistic regression; Least Absolute Selection and Shrinkage Operator (LASSO)

…model selection and shrinkage estimation for linear regression. To explain LASSO in the linear… …coefficient. In each graph we plot the coefficient from a logistic regression of a variable xi… …a set X and z for the raw data vs. the OR for the modeled standard regression data… …purchases behavior. Logistic regression is commonly used in predictive models based on household… …and build their own logistic normal regression with more of a focus on demographics and… 

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APA (6th Edition):

Condon, E. (2012). Varying Coefficients in Logistic Regression with Applications to Marketing Research. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/30947

Chicago Manual of Style (16th Edition):

Condon, Erin. “Varying Coefficients in Logistic Regression with Applications to Marketing Research.” 2012. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed June 25, 2019. http://hdl.handle.net/2142/30947.

MLA Handbook (7th Edition):

Condon, Erin. “Varying Coefficients in Logistic Regression with Applications to Marketing Research.” 2012. Web. 25 Jun 2019.

Vancouver:

Condon E. Varying Coefficients in Logistic Regression with Applications to Marketing Research. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2012. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/2142/30947.

Council of Science Editors:

Condon E. Varying Coefficients in Logistic Regression with Applications to Marketing Research. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2012. Available from: http://hdl.handle.net/2142/30947


University of Florida

17. Liu, Yanjun. Strength, Modulus of Elasticity, Shrinkage and Creep of Concrete.

Degree: PhD, Civil Engineering - Civil and Coastal Engineering, 2007, University of Florida

 In the application of prestressed concrete, there are concerns on severe prestress loss caused mainly by elastic shortening, shrinkage and creep of concrete, which will… (more)

Subjects/Keywords: Cements; Compression bandages; Compressive strength; Construction aggregate; Granite; Modeling; Moduli of elasticity; Moisture content; Proportional limit; Tensile strength; aggregate, creep, gauge, modulus, prediction, regression, shrinkage, strength

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APA (6th Edition):

Liu, Y. (2007). Strength, Modulus of Elasticity, Shrinkage and Creep of Concrete. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0021579

Chicago Manual of Style (16th Edition):

Liu, Yanjun. “Strength, Modulus of Elasticity, Shrinkage and Creep of Concrete.” 2007. Doctoral Dissertation, University of Florida. Accessed June 25, 2019. http://ufdc.ufl.edu/UFE0021579.

MLA Handbook (7th Edition):

Liu, Yanjun. “Strength, Modulus of Elasticity, Shrinkage and Creep of Concrete.” 2007. Web. 25 Jun 2019.

Vancouver:

Liu Y. Strength, Modulus of Elasticity, Shrinkage and Creep of Concrete. [Internet] [Doctoral dissertation]. University of Florida; 2007. [cited 2019 Jun 25]. Available from: http://ufdc.ufl.edu/UFE0021579.

Council of Science Editors:

Liu Y. Strength, Modulus of Elasticity, Shrinkage and Creep of Concrete. [Doctoral Dissertation]. University of Florida; 2007. Available from: http://ufdc.ufl.edu/UFE0021579

18. Yu, Danni. Estimation of Variation For High-throughput Molecular Biological Experiments With Small Sample Size.

Degree: PhD, Statistics, 2013, Purdue University

  Motivation: In the quantification of molecular components, a large variation can affect and even potentially mislead the biological conclusions. Meanwhile, the high-throughput experiments often… (more)

Subjects/Keywords: shrinkage estimator of dispersion in negative binomial models; pure sciences; biological sciences; linear mixed effect models; linear quadratic regression model with random coefficients; Bioinformatics; Biostatistics; Statistics and Probability

…4.3.1 Per-fragment linear quadratic regression. . . . . . . . . . . . . 74 4.3.2 All… …fragment linear quadratic regression for a peptide. . . . . . 76 4.3.3 Evaluations… …cutoff, obtained with the shrinkage of variance as opposed to the proposed shrinkage of… …perPairDisp’: separate dispersion estimation and shrinkage for each subject. ‘poolDisp’: averaged… …per-subject method of moments estimates of dispersion, and a single shrinkage step of the… 

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

APA (6th Edition):

Yu, D. (2013). Estimation of Variation For High-throughput Molecular Biological Experiments With Small Sample Size. (Doctoral Dissertation). Purdue University. Retrieved from http://docs.lib.purdue.edu/open_access_dissertations/14

Chicago Manual of Style (16th Edition):

Yu, Danni. “Estimation of Variation For High-throughput Molecular Biological Experiments With Small Sample Size.” 2013. Doctoral Dissertation, Purdue University. Accessed June 25, 2019. http://docs.lib.purdue.edu/open_access_dissertations/14.

MLA Handbook (7th Edition):

Yu, Danni. “Estimation of Variation For High-throughput Molecular Biological Experiments With Small Sample Size.” 2013. Web. 25 Jun 2019.

Vancouver:

Yu D. Estimation of Variation For High-throughput Molecular Biological Experiments With Small Sample Size. [Internet] [Doctoral dissertation]. Purdue University; 2013. [cited 2019 Jun 25]. Available from: http://docs.lib.purdue.edu/open_access_dissertations/14.

Council of Science Editors:

Yu D. Estimation of Variation For High-throughput Molecular Biological Experiments With Small Sample Size. [Doctoral Dissertation]. Purdue University; 2013. Available from: http://docs.lib.purdue.edu/open_access_dissertations/14


Brno University of Technology

19. Beranová, Michaela. Aspekty zásob v maloobchodě: modely přirozených úbytků zásob a ztratného .

Degree: 2009, Brno University of Technology

 Disertační práce se zabývá problematikou stanovení objektivní výše normy přirozených úbytků zásob a ztratného v maloobchodě. V rámci disertační práce jsou zkoumány faktory, které ovlivňují… (more)

Subjects/Keywords: Fuzzy logika; maloobchod; manko; přirozené úbytky zásob; regresní analýza; škoda; ztratné; Fuzzy Logic; Retail Business; Shortage of Stock; Natural Shrinkage of Stock; Regression Analysis; Damage; Accidental Losses of Stock

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APA (6th Edition):

Beranová, M. (2009). Aspekty zásob v maloobchodě: modely přirozených úbytků zásob a ztratného . (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/1397

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):

Beranová, Michaela. “Aspekty zásob v maloobchodě: modely přirozených úbytků zásob a ztratného .” 2009. Thesis, Brno University of Technology. Accessed June 25, 2019. http://hdl.handle.net/11012/1397.

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

MLA Handbook (7th Edition):

Beranová, Michaela. “Aspekty zásob v maloobchodě: modely přirozených úbytků zásob a ztratného .” 2009. Web. 25 Jun 2019.

Vancouver:

Beranová M. Aspekty zásob v maloobchodě: modely přirozených úbytků zásob a ztratného . [Internet] [Thesis]. Brno University of Technology; 2009. [cited 2019 Jun 25]. Available from: http://hdl.handle.net/11012/1397.

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

Council of Science Editors:

Beranová M. Aspekty zásob v maloobchodě: modely přirozených úbytků zásob a ztratného . [Thesis]. Brno University of Technology; 2009. Available from: http://hdl.handle.net/11012/1397

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

.