Advanced search options

Sorted by: relevance · author · university · date | New search

You searched for `subject:(solution path case weight homotopy data perturbation optimism large margin classifier svm quantile regression)`

.
Showing records 1 – 30 of
69946 total matches.

◁ [1] [2] [3] [4] [5] … [2332] ▶

Search Limiters

Dates

- 2015 – 2019 (24155)
- 2010 – 2014 (25604)
- 2005 – 2009 (12479)
- 2000 – 2004 (4637)
- 1995 – 1999 (2775)
- 1990 – 1994 (1642)
- 1985 – 1989 (1483)
- 1980 – 1984 (1102)
- 1975 – 1979 (736)
- 1970 – 1974 (509)

Universities

- Brno University of Technology (2712)
- ETH Zürich (1744)
- University of Hong Kong (1672)
- University of Florida (1626)
- KTH (1608)
- Chalmers University of Technology (1077)
- University of São Paulo (1076)
- Virginia Tech (1054)
- Texas A&M University (881)
- NSYSU (868)
- Michigan State University (780)
- Georgia Tech (699)
- Hong Kong University of Science and Technology (696)
- National University of Singapore (613)
- The Ohio State University (613)

Department

- Computer Science (1365)
- Chalmers University of Technology / Department of Computer Science and Engineering (Chalmers) (1007)
- Electrical and Computer Engineering (719)
- Statistics (670)
- Electrical Engineering and Computer Science (EECS) (616)
- Informatique (592)
- Electrical Engineering (576)
- Information and Communication Technology (ICT) (522)
- Psychology (444)
- Mechanical Engineering (429)
- Informatics (365)
- Computer Science and Engineering (330)
- Mathematics (325)
- Civil Engineering (312)
- Economics (279)

Degrees

Levels

- doctoral (20919)
- masters (12909)
- thesis (961)
- project (110)
- doctor of philosophy ph.d. (88)
- dissertation (82)
- doctor of philosophy (ph.d.) (46)
- open access (23)
- capstone (19)
- project/capstone (11)

Languages

Country

- US (24024)
- Sweden (6984)
- Canada (5118)
- Brazil (3362)
- France (3077)
- Czech Republic (2738)
- Australia (2455)
- Hong Kong (2372)
- South Africa (2309)
- UK (2129)
- Switzerland (1917)
- Portugal (1850)
- Netherlands (1617)
- Greece (1388)
- New Zealand (1089)

▼ Search Limiters

The Ohio State University

1.
TU, SHANSHAN.
* Case* Influence and Model Complexity in

Degree: PhD, Statistics, 2019, The Ohio State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1563324139376977

► *Case* influence and model complexity play very important roles in model diagnostics and model comparison. They have been extensively studied in linear *regression* and generalized…
(more)

Subjects/Keywords: Statistics; solution path, case weight, homotopy, data perturbation, optimism, large margin classifier, svm, quantile regression

Record Details Similar Records

❌

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

APA (6^{th} Edition):

TU, S. (2019). Case Influence and Model Complexity in Regression and Classification. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1563324139376977

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

TU, SHANSHAN. “Case Influence and Model Complexity in Regression and Classification.” 2019. Doctoral Dissertation, The Ohio State University. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1563324139376977.

MLA Handbook (7^{th} Edition):

TU, SHANSHAN. “Case Influence and Model Complexity in Regression and Classification.” 2019. Web. 17 Nov 2019.

Vancouver:

TU S. Case Influence and Model Complexity in Regression and Classification. [Internet] [Doctoral dissertation]. The Ohio State University; 2019. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1563324139376977.

Council of Science Editors:

TU S. Case Influence and Model Complexity in Regression and Classification. [Doctoral Dissertation]. The Ohio State University; 2019. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1563324139376977

University of Minnesota

2.
Peng, Bo.
Methodologies and Algorithms on Some Non-convex Penalized Models for Ultra High Dimensional * Data*.

Degree: PhD, Statistics, 2016, University of Minnesota

URL: http://hdl.handle.net/11299/182177

► In recent years, penalized models have gained considerable importance on deal- ing with variable selection and estimation problems under high dimensional settings. Of all the…
(more)

Subjects/Keywords: High dimensional data; Non-convex penalty; Oracle property; Quantile regression; SVM

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Peng, B. (2016). Methodologies and Algorithms on Some Non-convex Penalized Models for Ultra High Dimensional Data. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/182177

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

Peng, Bo. “Methodologies and Algorithms on Some Non-convex Penalized Models for Ultra High Dimensional Data.” 2016. Doctoral Dissertation, University of Minnesota. Accessed November 17, 2019. http://hdl.handle.net/11299/182177.

MLA Handbook (7^{th} Edition):

Peng, Bo. “Methodologies and Algorithms on Some Non-convex Penalized Models for Ultra High Dimensional Data.” 2016. Web. 17 Nov 2019.

Vancouver:

Peng B. Methodologies and Algorithms on Some Non-convex Penalized Models for Ultra High Dimensional Data. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/11299/182177.

Council of Science Editors:

Peng B. Methodologies and Algorithms on Some Non-convex Penalized Models for Ultra High Dimensional Data. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/182177

The Ohio State University

3. Yao, Yonggang. Statistical Applications of Linear Programming for Feature Selection via Regularization Methods.

Degree: PhD, Statistics, 2008, The Ohio State University

URL: http://rave.ohiolink.edu/etdc/view?acc_num=osu1222035715

► We consider statistical procedures for feature selection defined by a family of regularizationproblems with convex piecewise linear loss functions and penalties of <i>l</i>_{1} or <i>l</i>_{8}…
(more)

Subjects/Keywords: Statistics; variable selection; grouped variable selection; statistical regularization; parametric linear programming; simplex algorithm; tableau-simplex; solution path; support vector machine; quantile regression; Dantzig selector; functional component pursuit

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Yao, Y. (2008). Statistical Applications of Linear Programming for Feature Selection via Regularization Methods. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1222035715

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

Yao, Yonggang. “Statistical Applications of Linear Programming for Feature Selection via Regularization Methods.” 2008. Doctoral Dissertation, The Ohio State University. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1222035715.

MLA Handbook (7^{th} Edition):

Yao, Yonggang. “Statistical Applications of Linear Programming for Feature Selection via Regularization Methods.” 2008. Web. 17 Nov 2019.

Vancouver:

Yao Y. Statistical Applications of Linear Programming for Feature Selection via Regularization Methods. [Internet] [Doctoral dissertation]. The Ohio State University; 2008. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1222035715.

Council of Science Editors:

Yao Y. Statistical Applications of Linear Programming for Feature Selection via Regularization Methods. [Doctoral Dissertation]. The Ohio State University; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1222035715

University of Minnesota

4.
Gu, Yuwen.
Unconventional *Regression* for High-Dimensional *Data* Analysis.

Degree: PhD, Statistics, 2017, University of Minnesota

URL: http://hdl.handle.net/11299/206270

► Massive and complex *data* present new challenges that conventional sparse penalized mean regressions, such as the penalized least squares, cannot fully solve. For example, in…
(more)

Subjects/Keywords: ADMM; Asymmetric least squares; Composite quantile regression; High-dimensional data; Quantile regression; Sparse penalized regression

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Gu, Y. (2017). Unconventional Regression for High-Dimensional Data Analysis. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/206270

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

Gu, Yuwen. “Unconventional Regression for High-Dimensional Data Analysis.” 2017. Doctoral Dissertation, University of Minnesota. Accessed November 17, 2019. http://hdl.handle.net/11299/206270.

MLA Handbook (7^{th} Edition):

Gu, Yuwen. “Unconventional Regression for High-Dimensional Data Analysis.” 2017. Web. 17 Nov 2019.

Vancouver:

Gu Y. Unconventional Regression for High-Dimensional Data Analysis. [Internet] [Doctoral dissertation]. University of Minnesota; 2017. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/11299/206270.

Council of Science Editors:

Gu Y. Unconventional Regression for High-Dimensional Data Analysis. [Doctoral Dissertation]. University of Minnesota; 2017. Available from: http://hdl.handle.net/11299/206270

NSYSU

5. Ke, Yi-syuan. Forecast the M&A targets in IT industry using Support Vector Machine.

Degree: Master, Information Management, 2017, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0530117-140725

► In this era, companies are able to occupy a place in this vast market, but many companies face the change of market. They will lose…
(more)

Subjects/Keywords: M&A; Logistic Regression; Financial data; M&A-SVM model; SVM

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Ke, Y. (2017). Forecast the M&A targets in IT industry using Support Vector Machine. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0530117-140725

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

Not specified: Masters Thesis or Doctoral Dissertation

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

Ke, Yi-syuan. “Forecast the M&A targets in IT industry using Support Vector Machine.” 2017. Thesis, NSYSU. Accessed November 17, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0530117-140725.

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

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Ke, Yi-syuan. “Forecast the M&A targets in IT industry using Support Vector Machine.” 2017. Web. 17 Nov 2019.

Vancouver:

Ke Y. Forecast the M&A targets in IT industry using Support Vector Machine. [Internet] [Thesis]. NSYSU; 2017. [cited 2019 Nov 17]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0530117-140725.

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

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ke Y. Forecast the M&A targets in IT industry using Support Vector Machine. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0530117-140725

Not specified: Masters Thesis or Doctoral Dissertation

University of Georgia

6.
Santoso, Agung.
Predictors of educational attainment in Indonesia: comparing OLS *regression* and *quantile* *regression* approach.

Degree: MA, Educational Psychology, 2008, University of Georgia

URL: http://purl.galileo.usg.edu/uga_etd/santoso_agung_200812_ma

► The current study applied *quantile* *regression* analysis to estimate the relationship between educational attainment and its predictors, and compared the results to parameter estimates using…
(more)

Subjects/Keywords: quantile regression

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Santoso, A. (2008). Predictors of educational attainment in Indonesia: comparing OLS regression and quantile regression approach. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/santoso_agung_200812_ma

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

Santoso, Agung. “Predictors of educational attainment in Indonesia: comparing OLS regression and quantile regression approach.” 2008. Masters Thesis, University of Georgia. Accessed November 17, 2019. http://purl.galileo.usg.edu/uga_etd/santoso_agung_200812_ma.

MLA Handbook (7^{th} Edition):

Santoso, Agung. “Predictors of educational attainment in Indonesia: comparing OLS regression and quantile regression approach.” 2008. Web. 17 Nov 2019.

Vancouver:

Santoso A. Predictors of educational attainment in Indonesia: comparing OLS regression and quantile regression approach. [Internet] [Masters thesis]. University of Georgia; 2008. [cited 2019 Nov 17]. Available from: http://purl.galileo.usg.edu/uga_etd/santoso_agung_200812_ma.

Council of Science Editors:

Santoso A. Predictors of educational attainment in Indonesia: comparing OLS regression and quantile regression approach. [Masters Thesis]. University of Georgia; 2008. Available from: http://purl.galileo.usg.edu/uga_etd/santoso_agung_200812_ma

University of Florida

7.
Liu, Minzhao.
New Approaches for *Quantile* * Regression*.

Degree: PhD, Statistics, 2014, University of Florida

URL: http://ufdc.ufl.edu/UFE0046926

► *Quantile* *regression* is a powerful way to study the relationship between covariates and responses. Various approaches have been proposed to estimate *quantile* *regression* models. However,…
(more)

Subjects/Keywords: Gaussian distributions; Inference; Missing data; Parametric models; Quantile regression; Quantiles; Regression analysis; Regression coefficients; Statistics; Uniform Resource Locators; quantile

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Liu, M. (2014). New Approaches for Quantile Regression. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0046926

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

Liu, Minzhao. “New Approaches for Quantile Regression.” 2014. Doctoral Dissertation, University of Florida. Accessed November 17, 2019. http://ufdc.ufl.edu/UFE0046926.

MLA Handbook (7^{th} Edition):

Liu, Minzhao. “New Approaches for Quantile Regression.” 2014. Web. 17 Nov 2019.

Vancouver:

Liu M. New Approaches for Quantile Regression. [Internet] [Doctoral dissertation]. University of Florida; 2014. [cited 2019 Nov 17]. Available from: http://ufdc.ufl.edu/UFE0046926.

Council of Science Editors:

Liu M. New Approaches for Quantile Regression. [Doctoral Dissertation]. University of Florida; 2014. Available from: http://ufdc.ufl.edu/UFE0046926

Indian Institute of Science

8.
Bapat, Tanuja.
Sparse Multiclass And Multi-Label *Classifier* Design For Faster Inference.

Degree: 2011, Indian Institute of Science

URL: http://hdl.handle.net/2005/2065

► Many real-world problems like hand-written digit recognition or semantic scene classiﬁcation are treated as multiclass or multi-label classiﬁcation prob-lems. Solutions to these problems using support…
(more)

Subjects/Keywords: Artificial Intelligence; Machine Learning; Multiclass Classification; Multi-label Classification; Sparse Max-Margin Multiclass Classifier Design; Sparse Max-Margin Classifiers; Sparse Max-Margin Multi-label Classifier Design; Support Vector Machine (SVM); Sparse Classifiers; Computer Science

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Bapat, T. (2011). Sparse Multiclass And Multi-Label Classifier Design For Faster Inference. (Thesis). Indian Institute of Science. Retrieved from http://hdl.handle.net/2005/2065

Not specified: Masters Thesis or Doctoral Dissertation

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

Bapat, Tanuja. “Sparse Multiclass And Multi-Label Classifier Design For Faster Inference.” 2011. Thesis, Indian Institute of Science. Accessed November 17, 2019. http://hdl.handle.net/2005/2065.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Bapat, Tanuja. “Sparse Multiclass And Multi-Label Classifier Design For Faster Inference.” 2011. Web. 17 Nov 2019.

Vancouver:

Bapat T. Sparse Multiclass And Multi-Label Classifier Design For Faster Inference. [Internet] [Thesis]. Indian Institute of Science; 2011. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/2005/2065.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bapat T. Sparse Multiclass And Multi-Label Classifier Design For Faster Inference. [Thesis]. Indian Institute of Science; 2011. Available from: http://hdl.handle.net/2005/2065

Not specified: Masters Thesis or Doctoral Dissertation

Indian Institute of Science

9.
Bapat, Tanuja.
Sparse Multiclass And Multi-Label *Classifier* Design For Faster Inference.

Degree: 2011, Indian Institute of Science

URL: http://etd.iisc.ernet.in/handle/2005/2065 ; http://etd.ncsi.iisc.ernet.in/abstracts/2661/G24953-Abs.pdf

► Many real-world problems like hand-written digit recognition or semantic scene classiﬁcation are treated as multiclass or multi-label classiﬁcation prob-lems. Solutions to these problems using support…
(more)

Subjects/Keywords: Artificial Intelligence; Machine Learning; Multiclass Classification; Multi-label Classification; Sparse Max-Margin Multiclass Classifier Design; Sparse Max-Margin Classifiers; Sparse Max-Margin Multi-label Classifier Design; Support Vector Machine (SVM); Sparse Classifiers; Computer Science

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Bapat, T. (2011). Sparse Multiclass And Multi-Label Classifier Design For Faster Inference. (Thesis). Indian Institute of Science. Retrieved from http://etd.iisc.ernet.in/handle/2005/2065 ; http://etd.ncsi.iisc.ernet.in/abstracts/2661/G24953-Abs.pdf

Not specified: Masters Thesis or Doctoral Dissertation

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

Bapat, Tanuja. “Sparse Multiclass And Multi-Label Classifier Design For Faster Inference.” 2011. Thesis, Indian Institute of Science. Accessed November 17, 2019. http://etd.iisc.ernet.in/handle/2005/2065 ; http://etd.ncsi.iisc.ernet.in/abstracts/2661/G24953-Abs.pdf.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Bapat, Tanuja. “Sparse Multiclass And Multi-Label Classifier Design For Faster Inference.” 2011. Web. 17 Nov 2019.

Vancouver:

Bapat T. Sparse Multiclass And Multi-Label Classifier Design For Faster Inference. [Internet] [Thesis]. Indian Institute of Science; 2011. [cited 2019 Nov 17]. Available from: http://etd.iisc.ernet.in/handle/2005/2065 ; http://etd.ncsi.iisc.ernet.in/abstracts/2661/G24953-Abs.pdf.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Bapat T. Sparse Multiclass And Multi-Label Classifier Design For Faster Inference. [Thesis]. Indian Institute of Science; 2011. Available from: http://etd.iisc.ernet.in/handle/2005/2065 ; http://etd.ncsi.iisc.ernet.in/abstracts/2661/G24953-Abs.pdf

Not specified: Masters Thesis or Doctoral Dissertation

AUT University

10.
Ji, Xingxiu.
Geometric correlation extraction method for intelligent finance *data* analysis
.

Degree: 2012, AUT University

URL: http://hdl.handle.net/10292/4749

► Trend forecasting could be one of the most challenging things in stock market analysis, as the *data* associated with stock is the time series *data*…
(more)

Subjects/Keywords: Stock market prediction; SVM regression; Stock market analysis; Nonlinear prediction; Stock data correlation; Correlation SVM

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Ji, X. (2012). Geometric correlation extraction method for intelligent finance data analysis . (Thesis). AUT University. Retrieved from http://hdl.handle.net/10292/4749

Not specified: Masters Thesis or Doctoral Dissertation

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

Ji, Xingxiu. “Geometric correlation extraction method for intelligent finance data analysis .” 2012. Thesis, AUT University. Accessed November 17, 2019. http://hdl.handle.net/10292/4749.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Ji, Xingxiu. “Geometric correlation extraction method for intelligent finance data analysis .” 2012. Web. 17 Nov 2019.

Vancouver:

Ji X. Geometric correlation extraction method for intelligent finance data analysis . [Internet] [Thesis]. AUT University; 2012. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/10292/4749.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ji X. Geometric correlation extraction method for intelligent finance data analysis . [Thesis]. AUT University; 2012. Available from: http://hdl.handle.net/10292/4749

Not specified: Masters Thesis or Doctoral Dissertation

University of Akron

11.
Shaik Abdul, Ameer Basha.
* SVM* Classification and Analysis of

Degree: MS, Computer Science, 2011, University of Akron

URL: http://rave.ohiolink.edu/etdc/view?acc_num=akron1302618924

► Support vector machine is statistical classification algorithm that classifies *data* by separating two classes with the help of a functional hyper plane. *SVM* is known…
(more)

Subjects/Keywords: Bioinformatics; Computer Science; SVM; Data mining; classification; microarray; support vectors; margin distance

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Shaik Abdul, A. B. (2011). SVM Classification and Analysis of Margin Distance on Microarray Data. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1302618924

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

Shaik Abdul, Ameer Basha. “SVM Classification and Analysis of Margin Distance on Microarray Data.” 2011. Masters Thesis, University of Akron. Accessed November 17, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1302618924.

MLA Handbook (7^{th} Edition):

Shaik Abdul, Ameer Basha. “SVM Classification and Analysis of Margin Distance on Microarray Data.” 2011. Web. 17 Nov 2019.

Vancouver:

Shaik Abdul AB. SVM Classification and Analysis of Margin Distance on Microarray Data. [Internet] [Masters thesis]. University of Akron; 2011. [cited 2019 Nov 17]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1302618924.

Council of Science Editors:

Shaik Abdul AB. SVM Classification and Analysis of Margin Distance on Microarray Data. [Masters Thesis]. University of Akron; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1302618924

NSYSU

12. Yeh, Yen-Chen. The Influence of Tax Reduction in China`s 12th Five-Year Plan on Domestic Consumption.

Degree: Master, ICAPS, 2017, NSYSU

URL: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616117-200154

► Due to decrease of Chinaâs economic growth speed, Chinese government conduct a series of revolution. This paper focus on the inspection of the influence of…
(more)

Subjects/Keywords: income tax; value-added tax; domestic consumption; Panel data; quantile-regression

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Yeh, Y. (2017). The Influence of Tax Reduction in China`s 12th Five-Year Plan on Domestic Consumption. (Thesis). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616117-200154

Not specified: Masters Thesis or Doctoral Dissertation

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

Yeh, Yen-Chen. “The Influence of Tax Reduction in China`s 12th Five-Year Plan on Domestic Consumption.” 2017. Thesis, NSYSU. Accessed November 17, 2019. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616117-200154.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Yeh, Yen-Chen. “The Influence of Tax Reduction in China`s 12th Five-Year Plan on Domestic Consumption.” 2017. Web. 17 Nov 2019.

Vancouver:

Yeh Y. The Influence of Tax Reduction in China`s 12th Five-Year Plan on Domestic Consumption. [Internet] [Thesis]. NSYSU; 2017. [cited 2019 Nov 17]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616117-200154.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Yeh Y. The Influence of Tax Reduction in China`s 12th Five-Year Plan on Domestic Consumption. [Thesis]. NSYSU; 2017. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0616117-200154

Not specified: Masters Thesis or Doctoral Dissertation

University of Minnesota

13.
Sherwood, Benjamin Stanley.
*Quantile**regression* model selection.

Degree: PhD, Statistics, 2014, University of Minnesota

URL: http://hdl.handle.net/11299/163910

► *Quantile* *regression* models the conditional *quantile* of a response variable. Compared to least squares, which focuses on the conditional mean, it provides a more complete…
(more)

Subjects/Keywords: Missing data; Model selection; Partial linear; Quantile regression; SCAD; Semiparametric

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Sherwood, B. S. (2014). Quantile regression model selection. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/163910

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

Sherwood, Benjamin Stanley. “Quantile regression model selection.” 2014. Doctoral Dissertation, University of Minnesota. Accessed November 17, 2019. http://hdl.handle.net/11299/163910.

MLA Handbook (7^{th} Edition):

Sherwood, Benjamin Stanley. “Quantile regression model selection.” 2014. Web. 17 Nov 2019.

Vancouver:

Sherwood BS. Quantile regression model selection. [Internet] [Doctoral dissertation]. University of Minnesota; 2014. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/11299/163910.

Council of Science Editors:

Sherwood BS. Quantile regression model selection. [Doctoral Dissertation]. University of Minnesota; 2014. Available from: http://hdl.handle.net/11299/163910

University of Texas – Austin

14.
Xu, Jing, M.S. in Statistics.
Predict house prices using *quantile* * regression*.

Degree: MSin Statistics, Statistics, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/67630

► *Quantile* *Regression* Model (QRM), introduced by Koenker and Bassett in 1978, is a well-established and widely used technique in theoretical and applied statistics. QRM is…
(more)

Subjects/Keywords: Quantile regression; Variable selection; Bayesian Quantile Regression; Quantile regression forest

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Xu, Jing, M. S. i. S. (2018). Predict house prices using quantile regression. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/67630

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

Xu, Jing, M S in Statistics. “Predict house prices using quantile regression.” 2018. Masters Thesis, University of Texas – Austin. Accessed November 17, 2019. http://hdl.handle.net/2152/67630.

MLA Handbook (7^{th} Edition):

Xu, Jing, M S in Statistics. “Predict house prices using quantile regression.” 2018. Web. 17 Nov 2019.

Vancouver:

Xu, Jing MSiS. Predict house prices using quantile regression. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/2152/67630.

Council of Science Editors:

Xu, Jing MSiS. Predict house prices using quantile regression. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/67630

Brunel University

15.
Bin Muhd Noor, Nik Nooruhafidzi.
Statistical modelling of ECDA *data* for the prioritisation of defects on buried pipelines.

Degree: PhD, 2017, Brunel University

URL: http://bura.brunel.ac.uk/handle/2438/16392 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764926

► Buried pipelines are vulnerable to the threat of corrosion. Hence, they are normally coated with a protective coating to isolate the metal substrate from the…
(more)

Subjects/Keywords: Quantile regression; Bayesian quantile regression; Logistic quantile regression; Logistic regression; Pipeline coating defect size estimation

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Bin Muhd Noor, N. N. (2017). Statistical modelling of ECDA data for the prioritisation of defects on buried pipelines. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/16392 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764926

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

Bin Muhd Noor, Nik Nooruhafidzi. “Statistical modelling of ECDA data for the prioritisation of defects on buried pipelines.” 2017. Doctoral Dissertation, Brunel University. Accessed November 17, 2019. http://bura.brunel.ac.uk/handle/2438/16392 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764926.

MLA Handbook (7^{th} Edition):

Bin Muhd Noor, Nik Nooruhafidzi. “Statistical modelling of ECDA data for the prioritisation of defects on buried pipelines.” 2017. Web. 17 Nov 2019.

Vancouver:

Bin Muhd Noor NN. Statistical modelling of ECDA data for the prioritisation of defects on buried pipelines. [Internet] [Doctoral dissertation]. Brunel University; 2017. [cited 2019 Nov 17]. Available from: http://bura.brunel.ac.uk/handle/2438/16392 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764926.

Council of Science Editors:

Bin Muhd Noor NN. Statistical modelling of ECDA data for the prioritisation of defects on buried pipelines. [Doctoral Dissertation]. Brunel University; 2017. Available from: http://bura.brunel.ac.uk/handle/2438/16392 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764926

University of Alberta

16.
Hassan, Imran.
Hierarchical *Quantile* * Regression*.

Degree: MS, Department of Mathematical and Statistical Sciences, 2014, University of Alberta

URL: https://era.library.ualberta.ca/files/m326m3245

► *Quantile* *regression* supplements the ordinary least squares *regression* and provides a complete view of a relationship between a response variable and a set of covariates.…
(more)

Subjects/Keywords: quantile regression; Markov Chain Monte Carlo; asymmetric Laplace distribution; data cloning; Bayesian statistics; hierarchical models

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Hassan, I. (2014). Hierarchical Quantile Regression. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/m326m3245

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

Hassan, Imran. “Hierarchical Quantile Regression.” 2014. Masters Thesis, University of Alberta. Accessed November 17, 2019. https://era.library.ualberta.ca/files/m326m3245.

MLA Handbook (7^{th} Edition):

Hassan, Imran. “Hierarchical Quantile Regression.” 2014. Web. 17 Nov 2019.

Vancouver:

Hassan I. Hierarchical Quantile Regression. [Internet] [Masters thesis]. University of Alberta; 2014. [cited 2019 Nov 17]. Available from: https://era.library.ualberta.ca/files/m326m3245.

Council of Science Editors:

Hassan I. Hierarchical Quantile Regression. [Masters Thesis]. University of Alberta; 2014. Available from: https://era.library.ualberta.ca/files/m326m3245

Penn State University

17.
Kim, Seonjin.
Three essays on nonparametric inference for longitudinal
*data* and time series *data*.

Degree: PhD, Statistics, 2013, Penn State University

URL: https://etda.libraries.psu.edu/catalog/18557

► This thesis consists of three essays on nonparametric inference problems for dependent *data*, such as longitudinal *data* and time series *data*. In the literature on…
(more)

Subjects/Keywords: Locally stationary process; Longitudinal data; Measurement errors; Nonparametric inference; Quantile regression; Time series

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Kim, S. (2013). Three essays on nonparametric inference for longitudinal data and time series data. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/18557

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

Kim, Seonjin. “Three essays on nonparametric inference for longitudinal data and time series data.” 2013. Doctoral Dissertation, Penn State University. Accessed November 17, 2019. https://etda.libraries.psu.edu/catalog/18557.

MLA Handbook (7^{th} Edition):

Kim, Seonjin. “Three essays on nonparametric inference for longitudinal data and time series data.” 2013. Web. 17 Nov 2019.

Vancouver:

Kim S. Three essays on nonparametric inference for longitudinal data and time series data. [Internet] [Doctoral dissertation]. Penn State University; 2013. [cited 2019 Nov 17]. Available from: https://etda.libraries.psu.edu/catalog/18557.

Council of Science Editors:

Kim S. Three essays on nonparametric inference for longitudinal data and time series data. [Doctoral Dissertation]. Penn State University; 2013. Available from: https://etda.libraries.psu.edu/catalog/18557

Iowa State University

18.
Fostvedt, Luke Karsten.
Mixed effects modeling with missing *data* using *quantile* *regression* and joint modeling.

Degree: 2014, Iowa State University

URL: https://lib.dr.iastate.edu/etd/14153

► This thesis focuses on many different modeling approaches that can be used to evaluate *large* education *data* sets. In education research, it is common to…
(more)

Subjects/Keywords: Statistics; education data; Mixed effects modeling; multiple imputation; Quantile Regression; Education; Mathematics

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Fostvedt, L. K. (2014). Mixed effects modeling with missing data using quantile regression and joint modeling. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/14153

Not specified: Masters Thesis or Doctoral Dissertation

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

Fostvedt, Luke Karsten. “Mixed effects modeling with missing data using quantile regression and joint modeling.” 2014. Thesis, Iowa State University. Accessed November 17, 2019. https://lib.dr.iastate.edu/etd/14153.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Fostvedt, Luke Karsten. “Mixed effects modeling with missing data using quantile regression and joint modeling.” 2014. Web. 17 Nov 2019.

Vancouver:

Fostvedt LK. Mixed effects modeling with missing data using quantile regression and joint modeling. [Internet] [Thesis]. Iowa State University; 2014. [cited 2019 Nov 17]. Available from: https://lib.dr.iastate.edu/etd/14153.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Fostvedt LK. Mixed effects modeling with missing data using quantile regression and joint modeling. [Thesis]. Iowa State University; 2014. Available from: https://lib.dr.iastate.edu/etd/14153

Not specified: Masters Thesis or Doctoral Dissertation

University of Southern California

19.
Chang, Chih-Chieh.
Bayesian multilevel *quantile* *regression* for longitudinal
* data*.

Degree: PhD, Biostatistics, 2015, University of Southern California

URL: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/532589/rec/1043

► Conventional mixed effects *regression* focuses only on effects on the conditional mean, which may be inappropriate when the interest is in testing the effects on…
(more)

Subjects/Keywords: Bayesian; multilevel modeling; mixed-effect modeling; quantile regression; longitudinal data; childhood obesity

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Chang, C. (2015). Bayesian multilevel quantile regression for longitudinal data. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/532589/rec/1043

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

Chang, Chih-Chieh. “Bayesian multilevel quantile regression for longitudinal data.” 2015. Doctoral Dissertation, University of Southern California. Accessed November 17, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/532589/rec/1043.

MLA Handbook (7^{th} Edition):

Chang, Chih-Chieh. “Bayesian multilevel quantile regression for longitudinal data.” 2015. Web. 17 Nov 2019.

Vancouver:

Chang C. Bayesian multilevel quantile regression for longitudinal data. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2019 Nov 17]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/532589/rec/1043.

Council of Science Editors:

Chang C. Bayesian multilevel quantile regression for longitudinal data. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/532589/rec/1043

Brunel University

20.
Peluso, Alina.
Novel *regression* models for discrete response.

Degree: PhD, 2017, Brunel University

URL: http://bura.brunel.ac.uk/handle/2438/15581 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764827

► In a *regression* context, the aim is to analyse a response variable of interest conditional to a set of covariates. In many applications the response…
(more)

Subjects/Keywords: Discrete Weibull; Count data; Difference-in-differences; Multilevel model; Parametric quantile regression model

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Peluso, A. (2017). Novel regression models for discrete response. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/15581 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764827

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

Peluso, Alina. “Novel regression models for discrete response.” 2017. Doctoral Dissertation, Brunel University. Accessed November 17, 2019. http://bura.brunel.ac.uk/handle/2438/15581 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764827.

MLA Handbook (7^{th} Edition):

Peluso, Alina. “Novel regression models for discrete response.” 2017. Web. 17 Nov 2019.

Vancouver:

Peluso A. Novel regression models for discrete response. [Internet] [Doctoral dissertation]. Brunel University; 2017. [cited 2019 Nov 17]. Available from: http://bura.brunel.ac.uk/handle/2438/15581 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764827.

Council of Science Editors:

Peluso A. Novel regression models for discrete response. [Doctoral Dissertation]. Brunel University; 2017. Available from: http://bura.brunel.ac.uk/handle/2438/15581 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764827

University of New South Wales

21.
Rodrigues, Thais Carvalho Valadares.
Pyramid *Quantile* * Regression*.

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

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

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

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

Record Details Similar Records

❌

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

APA (6^{th} Edition):

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

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

Rodrigues, Thais Carvalho Valadares. “Pyramid Quantile Regression.” 2017. Doctoral Dissertation, University of New South Wales. Accessed November 17, 2019. http://handle.unsw.edu.au/1959.4/58446 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46045/SOURCE02?view=true.

MLA Handbook (7^{th} Edition):

Rodrigues, Thais Carvalho Valadares. “Pyramid Quantile Regression.” 2017. Web. 17 Nov 2019.

Vancouver:

Rodrigues TCV. Pyramid Quantile Regression. [Internet] [Doctoral dissertation]. University of New South Wales; 2017. [cited 2019 Nov 17]. Available from: http://handle.unsw.edu.au/1959.4/58446 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:46045/SOURCE02?view=true.

Council of Science Editors:

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

University of Waterloo

22.
Huang, Shimeng.
Empirical Likelihood *Quantile* *Regression* for Right-Censored * Data*.

Degree: 2018, University of Waterloo

URL: http://hdl.handle.net/10012/14253

► *Quantile* estimation of time-to-event *data* plays a key role in many medical applications, especially conditional on covariates of interest. In such settings, bias due to…
(more)

Subjects/Keywords: Empirical likelihood; Quantile regression; EM algorithm; Length-biased data; Right-censoring; Continuity correction; Confidence intervals; Location-scale regression model

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Huang, S. (2018). Empirical Likelihood Quantile Regression for Right-Censored Data. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/14253

Not specified: Masters Thesis or Doctoral Dissertation

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

Huang, Shimeng. “Empirical Likelihood Quantile Regression for Right-Censored Data.” 2018. Thesis, University of Waterloo. Accessed November 17, 2019. http://hdl.handle.net/10012/14253.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Huang, Shimeng. “Empirical Likelihood Quantile Regression for Right-Censored Data.” 2018. Web. 17 Nov 2019.

Vancouver:

Huang S. Empirical Likelihood Quantile Regression for Right-Censored Data. [Internet] [Thesis]. University of Waterloo; 2018. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/10012/14253.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Huang S. Empirical Likelihood Quantile Regression for Right-Censored Data. [Thesis]. University of Waterloo; 2018. Available from: http://hdl.handle.net/10012/14253

Not specified: Masters Thesis or Doctoral Dissertation

University of South Carolina

23.
Wu, Junlong.
Methods For Constructing Confidence Intervals For *Quantile* *Regression* Coefficients.

Degree: PhD, Epidemiology and Biostatistics, 2011, University of South Carolina

URL: https://scholarcommons.sc.edu/etd/560

► We describe and compare methods for constructing confidence intervals for *quantile* *regression* coefficients. We consider methods based on resampling, sparsity estimation, and test-inversion. In…
(more)

Subjects/Keywords: Biostatistics; Physical Sciences and Mathematics; Statistics and Probability; bisection method; confidence interval; dependent data; logistic regression; quantile regression

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Wu, J. (2011). Methods For Constructing Confidence Intervals For Quantile Regression Coefficients. (Doctoral Dissertation). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/560

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

Wu, Junlong. “Methods For Constructing Confidence Intervals For Quantile Regression Coefficients.” 2011. Doctoral Dissertation, University of South Carolina. Accessed November 17, 2019. https://scholarcommons.sc.edu/etd/560.

MLA Handbook (7^{th} Edition):

Wu, Junlong. “Methods For Constructing Confidence Intervals For Quantile Regression Coefficients.” 2011. Web. 17 Nov 2019.

Vancouver:

Wu J. Methods For Constructing Confidence Intervals For Quantile Regression Coefficients. [Internet] [Doctoral dissertation]. University of South Carolina; 2011. [cited 2019 Nov 17]. Available from: https://scholarcommons.sc.edu/etd/560.

Council of Science Editors:

Wu J. Methods For Constructing Confidence Intervals For Quantile Regression Coefficients. [Doctoral Dissertation]. University of South Carolina; 2011. Available from: https://scholarcommons.sc.edu/etd/560

University of Alberta

24.
Shi, Qian.
Variable Screening Based on Combining *Quantile*
* Regression*.

Degree: MS, Department of Mathematical and Statistical Sciences, 2014, University of Alberta

URL: https://era.library.ualberta.ca/files/js956h083

► This thesis develops an efficient *quantile*-adaptive framework for linear and nonlinear variable screening with high-dimensional heterogeneous *data*. Inspired by the success of various variable screening…
(more)

Subjects/Keywords: quantile regression; average quantile regression; variable screening; composite quantile regression; B-spline approximations

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Shi, Q. (2014). Variable Screening Based on Combining Quantile Regression. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/js956h083

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

Shi, Qian. “Variable Screening Based on Combining Quantile Regression.” 2014. Masters Thesis, University of Alberta. Accessed November 17, 2019. https://era.library.ualberta.ca/files/js956h083.

MLA Handbook (7^{th} Edition):

Shi, Qian. “Variable Screening Based on Combining Quantile Regression.” 2014. Web. 17 Nov 2019.

Vancouver:

Shi Q. Variable Screening Based on Combining Quantile Regression. [Internet] [Masters thesis]. University of Alberta; 2014. [cited 2019 Nov 17]. Available from: https://era.library.ualberta.ca/files/js956h083.

Council of Science Editors:

Shi Q. Variable Screening Based on Combining Quantile Regression. [Masters Thesis]. University of Alberta; 2014. Available from: https://era.library.ualberta.ca/files/js956h083

25. Sandsveden, Daniel. Evaluation of Random Forests for Detection and Localization of Cattle Eyes.

Degree: Faculty of Science & Engineering, 2015, Linköping UniversityLinköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121540

► In a time when cattle herds grow continually larger the need for automatic methods to detect diseases is ever increasing. One possible method to…
(more)

Subjects/Keywords: Random Forests; HOG; LBP; SVM; Descriptor; Classifier

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Sandsveden, D. (2015). Evaluation of Random Forests for Detection and Localization of Cattle Eyes. (Thesis). Linköping UniversityLinköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121540

Not specified: Masters Thesis or Doctoral Dissertation

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

Sandsveden, Daniel. “Evaluation of Random Forests for Detection and Localization of Cattle Eyes.” 2015. Thesis, Linköping UniversityLinköping University. Accessed November 17, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121540.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Sandsveden, Daniel. “Evaluation of Random Forests for Detection and Localization of Cattle Eyes.” 2015. Web. 17 Nov 2019.

Vancouver:

Sandsveden D. Evaluation of Random Forests for Detection and Localization of Cattle Eyes. [Internet] [Thesis]. Linköping UniversityLinköping University; 2015. [cited 2019 Nov 17]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121540.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sandsveden D. Evaluation of Random Forests for Detection and Localization of Cattle Eyes. [Thesis]. Linköping UniversityLinköping University; 2015. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121540

Not specified: Masters Thesis or Doctoral Dissertation

University of Manchester

26.
Kecojevic, Tatjana.
Bootstrap inference for parametric *quantile* * regression*.

Degree: PhD, 2011, University of Manchester

URL: https://www.research.manchester.ac.uk/portal/en/theses/bootstrap-inference-for-parametric-quantile-regression(194021d5-e03f-4f48-bfb8-5156819f5900).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549093

► The motivation for this thesis came from the provision of a *large* *data* set from Saudi Arabia giving anthropometric measurements of children and adolescents from…
(more)

Subjects/Keywords: 519; Quantile Regression; Bootstrapping

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Kecojevic, T. (2011). Bootstrap inference for parametric quantile regression. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/bootstrap-inference-for-parametric-quantile-regression(194021d5-e03f-4f48-bfb8-5156819f5900).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549093

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

Kecojevic, Tatjana. “Bootstrap inference for parametric quantile regression.” 2011. Doctoral Dissertation, University of Manchester. Accessed November 17, 2019. https://www.research.manchester.ac.uk/portal/en/theses/bootstrap-inference-for-parametric-quantile-regression(194021d5-e03f-4f48-bfb8-5156819f5900).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549093.

MLA Handbook (7^{th} Edition):

Kecojevic, Tatjana. “Bootstrap inference for parametric quantile regression.” 2011. Web. 17 Nov 2019.

Vancouver:

Kecojevic T. Bootstrap inference for parametric quantile regression. [Internet] [Doctoral dissertation]. University of Manchester; 2011. [cited 2019 Nov 17]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/bootstrap-inference-for-parametric-quantile-regression(194021d5-e03f-4f48-bfb8-5156819f5900).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549093.

Council of Science Editors:

Kecojevic T. Bootstrap inference for parametric quantile regression. [Doctoral Dissertation]. University of Manchester; 2011. Available from: https://www.research.manchester.ac.uk/portal/en/theses/bootstrap-inference-for-parametric-quantile-regression(194021d5-e03f-4f48-bfb8-5156819f5900).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.549093

Virginia Tech

27. Zhang, Dengfeng. Latent Class Model in Transportation Study.

Degree: PhD, Statistics, 2015, Virginia Tech

URL: http://hdl.handle.net/10919/51203

► Statistics, as a critical component in transportation research, has been widely used to analyze driver safety, travel time, traffic flow and numerous other problems. Many…
(more)

Subjects/Keywords: Transportation; Mixture model; Quantile regression

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Zhang, D. (2015). Latent Class Model in Transportation Study. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51203

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

Zhang, Dengfeng. “Latent Class Model in Transportation Study.” 2015. Doctoral Dissertation, Virginia Tech. Accessed November 17, 2019. http://hdl.handle.net/10919/51203.

MLA Handbook (7^{th} Edition):

Zhang, Dengfeng. “Latent Class Model in Transportation Study.” 2015. Web. 17 Nov 2019.

Vancouver:

Zhang D. Latent Class Model in Transportation Study. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2019 Nov 17]. Available from: http://hdl.handle.net/10919/51203.

Council of Science Editors:

Zhang D. Latent Class Model in Transportation Study. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/51203

Boston College

28. Jiang, Chuanliang. Three Essays In Finance Economics.

Degree: PhD, Economics, 2013, Boston College

URL: http://dlib.bc.edu/islandora/object/bc-ir:101945

► This dissertation contains three essays. It provides an application of *quantile* *regression* in Financial Economics. The first essay investigates whether tail dependence makes a difference…
(more)

Subjects/Keywords: Financial economics; Quantile regression

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Jiang, C. (2013). Three Essays In Finance Economics. (Doctoral Dissertation). Boston College. Retrieved from http://dlib.bc.edu/islandora/object/bc-ir:101945

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

Jiang, Chuanliang. “Three Essays In Finance Economics.” 2013. Doctoral Dissertation, Boston College. Accessed November 17, 2019. http://dlib.bc.edu/islandora/object/bc-ir:101945.

MLA Handbook (7^{th} Edition):

Jiang, Chuanliang. “Three Essays In Finance Economics.” 2013. Web. 17 Nov 2019.

Vancouver:

Jiang C. Three Essays In Finance Economics. [Internet] [Doctoral dissertation]. Boston College; 2013. [cited 2019 Nov 17]. Available from: http://dlib.bc.edu/islandora/object/bc-ir:101945.

Council of Science Editors:

Jiang C. Three Essays In Finance Economics. [Doctoral Dissertation]. Boston College; 2013. Available from: http://dlib.bc.edu/islandora/object/bc-ir:101945

Boston College

29.
Sim, Nicholas.
Modeling *Quantile* Dependence.

Degree: PhD, Economics, 2009, Boston College

URL: http://dlib.bc.edu/islandora/object/bc-ir:101409

► In recent years, *quantile* *regression* has achieved increasing prominence as a quantitative method of choice in applied econometric research. The methodology focuses on how the…
(more)

Subjects/Keywords: Monetary Policy; Quantile Regression; Quantile-Quantile Model; Stock Returns Correlation

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Sim, N. (2009). Modeling Quantile Dependence. (Doctoral Dissertation). Boston College. Retrieved from http://dlib.bc.edu/islandora/object/bc-ir:101409

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

Sim, Nicholas. “Modeling Quantile Dependence.” 2009. Doctoral Dissertation, Boston College. Accessed November 17, 2019. http://dlib.bc.edu/islandora/object/bc-ir:101409.

MLA Handbook (7^{th} Edition):

Sim, Nicholas. “Modeling Quantile Dependence.” 2009. Web. 17 Nov 2019.

Vancouver:

Sim N. Modeling Quantile Dependence. [Internet] [Doctoral dissertation]. Boston College; 2009. [cited 2019 Nov 17]. Available from: http://dlib.bc.edu/islandora/object/bc-ir:101409.

Council of Science Editors:

Sim N. Modeling Quantile Dependence. [Doctoral Dissertation]. Boston College; 2009. Available from: http://dlib.bc.edu/islandora/object/bc-ir:101409

University of Florida

30.
Kodipaka, Santhosh.
A Novel Conic Section *Classifier* with Tractable Geometric Learning Algorithms.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2009, University of Florida

URL: http://ufdc.ufl.edu/UFE0024624

► Several pattern recognition problems in computer vision and medical diagnosis can be posed in the general framework of supervised learning. However, the high-dimensionality of the…
(more)

Subjects/Keywords: Conic sections; Datasets; Discriminants; Eggshells; Epilepsy; Hyperplanes; Hyperspheres; Learning; Machine learning; Polynomials; boundaries, class, classifier, concept, conic, constraints, design, discriminant, eccentricity, evaluation, geometry, large, learning, machine, margin, nonlinear, sections, stiffness

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Kodipaka, S. (2009). A Novel Conic Section Classifier with Tractable Geometric Learning Algorithms. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0024624

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

Kodipaka, Santhosh. “A Novel Conic Section Classifier with Tractable Geometric Learning Algorithms.” 2009. Doctoral Dissertation, University of Florida. Accessed November 17, 2019. http://ufdc.ufl.edu/UFE0024624.

MLA Handbook (7^{th} Edition):

Kodipaka, Santhosh. “A Novel Conic Section Classifier with Tractable Geometric Learning Algorithms.” 2009. Web. 17 Nov 2019.

Vancouver:

Kodipaka S. A Novel Conic Section Classifier with Tractable Geometric Learning Algorithms. [Internet] [Doctoral dissertation]. University of Florida; 2009. [cited 2019 Nov 17]. Available from: http://ufdc.ufl.edu/UFE0024624.

Council of Science Editors:

Kodipaka S. A Novel Conic Section Classifier with Tractable Geometric Learning Algorithms. [Doctoral Dissertation]. University of Florida; 2009. Available from: http://ufdc.ufl.edu/UFE0024624