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You searched for subject:(Error statistics). Showing records 1 – 30 of 174 total matches.

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University of Manchester

1. Pina Sanchez, Jose Maria. Prevalence, Impact, and Adjustments of Measurement Error in Retrospective Reports of Unemployment: An Analysis Using Swedish Administrative Data.

Degree: 2014, University of Manchester

 In this thesis I carry out an encompassing analysis of the problem of measurement error in retrospectively collected work histories using data from the “Longitudinal… (more)

Subjects/Keywords: Measurement Error; Survey Research; Unemployment; Bayesian Statistics

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

APA (6th Edition):

Pina Sanchez, J. M. (2014). Prevalence, Impact, and Adjustments of Measurement Error in Retrospective Reports of Unemployment: An Analysis Using Swedish Administrative Data. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:232708

Chicago Manual of Style (16th Edition):

Pina Sanchez, Jose Maria. “Prevalence, Impact, and Adjustments of Measurement Error in Retrospective Reports of Unemployment: An Analysis Using Swedish Administrative Data.” 2014. Doctoral Dissertation, University of Manchester. Accessed January 19, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:232708.

MLA Handbook (7th Edition):

Pina Sanchez, Jose Maria. “Prevalence, Impact, and Adjustments of Measurement Error in Retrospective Reports of Unemployment: An Analysis Using Swedish Administrative Data.” 2014. Web. 19 Jan 2021.

Vancouver:

Pina Sanchez JM. Prevalence, Impact, and Adjustments of Measurement Error in Retrospective Reports of Unemployment: An Analysis Using Swedish Administrative Data. [Internet] [Doctoral dissertation]. University of Manchester; 2014. [cited 2021 Jan 19]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:232708.

Council of Science Editors:

Pina Sanchez JM. Prevalence, Impact, and Adjustments of Measurement Error in Retrospective Reports of Unemployment: An Analysis Using Swedish Administrative Data. [Doctoral Dissertation]. University of Manchester; 2014. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:232708


Bowling Green State University

2. Shifa, Naima. Estimation of Qvf Measurement Error Models Using Empirical Likelihood Method.

Degree: PhD, Mathematics/Mathematical Statistics, 2009, Bowling Green State University

 Predictor variables are often contaminated with measurement errors in statistical practice. This may be the case due to bad measurement apparatus or just because the… (more)

Subjects/Keywords: Statistics; MEASUREMENT ERROR

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APA (6th Edition):

Shifa, N. (2009). Estimation of Qvf Measurement Error Models Using Empirical Likelihood Method. (Doctoral Dissertation). Bowling Green State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1245415705

Chicago Manual of Style (16th Edition):

Shifa, Naima. “Estimation of Qvf Measurement Error Models Using Empirical Likelihood Method.” 2009. Doctoral Dissertation, Bowling Green State University. Accessed January 19, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1245415705.

MLA Handbook (7th Edition):

Shifa, Naima. “Estimation of Qvf Measurement Error Models Using Empirical Likelihood Method.” 2009. Web. 19 Jan 2021.

Vancouver:

Shifa N. Estimation of Qvf Measurement Error Models Using Empirical Likelihood Method. [Internet] [Doctoral dissertation]. Bowling Green State University; 2009. [cited 2021 Jan 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1245415705.

Council of Science Editors:

Shifa N. Estimation of Qvf Measurement Error Models Using Empirical Likelihood Method. [Doctoral Dissertation]. Bowling Green State University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1245415705


The Ohio State University

3. Ball, Allen Dwayne. Individual differences multidimensional scaling and the nature of error in human judgments.

Degree: PhD, Graduate School, 1982, The Ohio State University

Subjects/Keywords: Statistics; Difference; Error

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APA (6th Edition):

Ball, A. D. (1982). Individual differences multidimensional scaling and the nature of error in human judgments. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1487172339758385

Chicago Manual of Style (16th Edition):

Ball, Allen Dwayne. “Individual differences multidimensional scaling and the nature of error in human judgments.” 1982. Doctoral Dissertation, The Ohio State University. Accessed January 19, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487172339758385.

MLA Handbook (7th Edition):

Ball, Allen Dwayne. “Individual differences multidimensional scaling and the nature of error in human judgments.” 1982. Web. 19 Jan 2021.

Vancouver:

Ball AD. Individual differences multidimensional scaling and the nature of error in human judgments. [Internet] [Doctoral dissertation]. The Ohio State University; 1982. [cited 2021 Jan 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1487172339758385.

Council of Science Editors:

Ball AD. Individual differences multidimensional scaling and the nature of error in human judgments. [Doctoral Dissertation]. The Ohio State University; 1982. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1487172339758385


University of Illinois – Urbana-Champaign

4. Lee, Yu-Hung. Characterization and Engineering of Error Statistics for Reliable Computation.

Degree: MS, 1200, 2011, University of Illinois – Urbana-Champaign

 We make a case for developing statistical error models of nanoscale circuits, employing these for designing robust systems, and engineering error-statistics to enhance the performance… (more)

Subjects/Keywords: robust system design; error statistics; diversity technique; error model

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APA (6th Edition):

Lee, Y. (2011). Characterization and Engineering of Error Statistics for Reliable Computation. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/18281

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):

Lee, Yu-Hung. “Characterization and Engineering of Error Statistics for Reliable Computation.” 2011. Thesis, University of Illinois – Urbana-Champaign. Accessed January 19, 2021. http://hdl.handle.net/2142/18281.

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

MLA Handbook (7th Edition):

Lee, Yu-Hung. “Characterization and Engineering of Error Statistics for Reliable Computation.” 2011. Web. 19 Jan 2021.

Vancouver:

Lee Y. Characterization and Engineering of Error Statistics for Reliable Computation. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2011. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/2142/18281.

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

Council of Science Editors:

Lee Y. Characterization and Engineering of Error Statistics for Reliable Computation. [Thesis]. University of Illinois – Urbana-Champaign; 2011. Available from: http://hdl.handle.net/2142/18281

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


University of Johannesburg

5. Musekiwa, Alfred. Estimating the slope in the simple linear errors-in-variables model.

Degree: 2012, University of Johannesburg

M.Sc.

In this study we consider the problem ofestiniating the slope in the simple linear errors-in-variables model. There are two different types of relationship that… (more)

Subjects/Keywords: Variables (Mathematics); Error analysis (Mathematics); Bootstrap (Statistics); Instrumental variables (Statistics)

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APA (6th Edition):

Musekiwa, A. (2012). Estimating the slope in the simple linear errors-in-variables model. (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/5493

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):

Musekiwa, Alfred. “Estimating the slope in the simple linear errors-in-variables model.” 2012. Thesis, University of Johannesburg. Accessed January 19, 2021. http://hdl.handle.net/10210/5493.

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

MLA Handbook (7th Edition):

Musekiwa, Alfred. “Estimating the slope in the simple linear errors-in-variables model.” 2012. Web. 19 Jan 2021.

Vancouver:

Musekiwa A. Estimating the slope in the simple linear errors-in-variables model. [Internet] [Thesis]. University of Johannesburg; 2012. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10210/5493.

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

Council of Science Editors:

Musekiwa A. Estimating the slope in the simple linear errors-in-variables model. [Thesis]. University of Johannesburg; 2012. Available from: http://hdl.handle.net/10210/5493

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


Michigan State University

6. Kaul, Abhishek. High dimensional linear regression models under long memory dependence and measurement error.

Degree: 2015, Michigan State University

Thesis Ph. D. Michigan State University. Statistics 2015

This dissertation consists of three chapters. The first chapter introduces the models under consideration and motivates problems… (more)

Subjects/Keywords: Regression analysis – Mathematical models; Error analysis (Mathematics); Mathematical statistics; Statistics

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APA (6th Edition):

Kaul, A. (2015). High dimensional linear regression models under long memory dependence and measurement error. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:3550

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):

Kaul, Abhishek. “High dimensional linear regression models under long memory dependence and measurement error.” 2015. Thesis, Michigan State University. Accessed January 19, 2021. http://etd.lib.msu.edu/islandora/object/etd:3550.

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

MLA Handbook (7th Edition):

Kaul, Abhishek. “High dimensional linear regression models under long memory dependence and measurement error.” 2015. Web. 19 Jan 2021.

Vancouver:

Kaul A. High dimensional linear regression models under long memory dependence and measurement error. [Internet] [Thesis]. Michigan State University; 2015. [cited 2021 Jan 19]. Available from: http://etd.lib.msu.edu/islandora/object/etd:3550.

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

Council of Science Editors:

Kaul A. High dimensional linear regression models under long memory dependence and measurement error. [Thesis]. Michigan State University; 2015. Available from: http://etd.lib.msu.edu/islandora/object/etd:3550

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


Temple University

7. Yang, Zijiang. New Step Down Procedures for Control of the Familywise Error Rate.

Degree: PhD, 2008, Temple University

Statistics

The main research topic in this dissertation is the development of the closure method of multiple testing procedures. Considering a general procedure that allows… (more)

Subjects/Keywords: Statistics; Multiple Comparisons; Familywise Error Rate; Generalized Familywise Error Rate; Closure Method; Step-down Test

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APA (6th Edition):

Yang, Z. (2008). New Step Down Procedures for Control of the Familywise Error Rate. (Doctoral Dissertation). Temple University. Retrieved from http://digital.library.temple.edu/u?/p245801coll10,20124

Chicago Manual of Style (16th Edition):

Yang, Zijiang. “New Step Down Procedures for Control of the Familywise Error Rate.” 2008. Doctoral Dissertation, Temple University. Accessed January 19, 2021. http://digital.library.temple.edu/u?/p245801coll10,20124.

MLA Handbook (7th Edition):

Yang, Zijiang. “New Step Down Procedures for Control of the Familywise Error Rate.” 2008. Web. 19 Jan 2021.

Vancouver:

Yang Z. New Step Down Procedures for Control of the Familywise Error Rate. [Internet] [Doctoral dissertation]. Temple University; 2008. [cited 2021 Jan 19]. Available from: http://digital.library.temple.edu/u?/p245801coll10,20124.

Council of Science Editors:

Yang Z. New Step Down Procedures for Control of the Familywise Error Rate. [Doctoral Dissertation]. Temple University; 2008. Available from: http://digital.library.temple.edu/u?/p245801coll10,20124


Western Kentucky University

8. Dai, Xiaogang. Score Test and Likelihood Ratio Test for Zero-Inflated Binomial Distribution and Geometric Distribution.

Degree: MS, Department of Mathematics, 2018, Western Kentucky University

  The main purpose of this thesis is to compare the performance of the score test and the likelihood ratio test by computing type I… (more)

Subjects/Keywords: Rao's score test; type I error; type II error; Applied Statistics; Other Applied Mathematics; Probability

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APA (6th Edition):

Dai, X. (2018). Score Test and Likelihood Ratio Test for Zero-Inflated Binomial Distribution and Geometric Distribution. (Masters Thesis). Western Kentucky University. Retrieved from https://digitalcommons.wku.edu/theses/2447

Chicago Manual of Style (16th Edition):

Dai, Xiaogang. “Score Test and Likelihood Ratio Test for Zero-Inflated Binomial Distribution and Geometric Distribution.” 2018. Masters Thesis, Western Kentucky University. Accessed January 19, 2021. https://digitalcommons.wku.edu/theses/2447.

MLA Handbook (7th Edition):

Dai, Xiaogang. “Score Test and Likelihood Ratio Test for Zero-Inflated Binomial Distribution and Geometric Distribution.” 2018. Web. 19 Jan 2021.

Vancouver:

Dai X. Score Test and Likelihood Ratio Test for Zero-Inflated Binomial Distribution and Geometric Distribution. [Internet] [Masters thesis]. Western Kentucky University; 2018. [cited 2021 Jan 19]. Available from: https://digitalcommons.wku.edu/theses/2447.

Council of Science Editors:

Dai X. Score Test and Likelihood Ratio Test for Zero-Inflated Binomial Distribution and Geometric Distribution. [Masters Thesis]. Western Kentucky University; 2018. Available from: https://digitalcommons.wku.edu/theses/2447

9. Ries, Daniel. Measurement error modeling of physical activity data.

Degree: 2017, Iowa State University

 Physical activity is an important component to a healthy lifestyle. However, it is difficult to create physical activity recommendations because it is difficult to track… (more)

Subjects/Keywords: Bayesian statistics; Measurement error; Physical activity; Reversible jump mcmc; Statistics and Probability

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

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APA (6th Edition):

Ries, D. (2017). Measurement error modeling of physical activity data. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/16449

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):

Ries, Daniel. “Measurement error modeling of physical activity data.” 2017. Thesis, Iowa State University. Accessed January 19, 2021. https://lib.dr.iastate.edu/etd/16449.

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

MLA Handbook (7th Edition):

Ries, Daniel. “Measurement error modeling of physical activity data.” 2017. Web. 19 Jan 2021.

Vancouver:

Ries D. Measurement error modeling of physical activity data. [Internet] [Thesis]. Iowa State University; 2017. [cited 2021 Jan 19]. Available from: https://lib.dr.iastate.edu/etd/16449.

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

Council of Science Editors:

Ries D. Measurement error modeling of physical activity data. [Thesis]. Iowa State University; 2017. Available from: https://lib.dr.iastate.edu/etd/16449

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


University of California – Berkeley

10. Long, James Patrick. Prediction Methods for Astronomical Data Observed with Measurement Error.

Degree: Statistics, 2013, University of California – Berkeley

 We study prediction when features are observed with measurement error. The research is motivated by classification challenges in astronomy.In Chapter 1 we introduce the periodic… (more)

Subjects/Keywords: Statistics; Astronomy; astrostatistics; classification; density estimation; measurement error; variable stars

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APA (6th Edition):

Long, J. P. (2013). Prediction Methods for Astronomical Data Observed with Measurement Error. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/0s79z3hk

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):

Long, James Patrick. “Prediction Methods for Astronomical Data Observed with Measurement Error.” 2013. Thesis, University of California – Berkeley. Accessed January 19, 2021. http://www.escholarship.org/uc/item/0s79z3hk.

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

MLA Handbook (7th Edition):

Long, James Patrick. “Prediction Methods for Astronomical Data Observed with Measurement Error.” 2013. Web. 19 Jan 2021.

Vancouver:

Long JP. Prediction Methods for Astronomical Data Observed with Measurement Error. [Internet] [Thesis]. University of California – Berkeley; 2013. [cited 2021 Jan 19]. Available from: http://www.escholarship.org/uc/item/0s79z3hk.

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

Council of Science Editors:

Long JP. Prediction Methods for Astronomical Data Observed with Measurement Error. [Thesis]. University of California – Berkeley; 2013. Available from: http://www.escholarship.org/uc/item/0s79z3hk

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


Rhodes University

11. Sharp, Gary David. Lag length selection for vector error correction models.

Degree: PhD, Faculty of Science, Statistics, 2010, Rhodes University

 This thesis investigates the problem of model identification in a Vector Autoregressive framework. The study reviews the existing research, conducts an extensive simulation based analysis… (more)

Subjects/Keywords: Akaike Information Criterion; Mathematical models  – Evaluation; Autoregression (Statistics); Error analysis (Mathematics)

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APA (6th Edition):

Sharp, G. D. (2010). Lag length selection for vector error correction models. (Doctoral Dissertation). Rhodes University. Retrieved from http://hdl.handle.net/10962/d1002808

Chicago Manual of Style (16th Edition):

Sharp, Gary David. “Lag length selection for vector error correction models.” 2010. Doctoral Dissertation, Rhodes University. Accessed January 19, 2021. http://hdl.handle.net/10962/d1002808.

MLA Handbook (7th Edition):

Sharp, Gary David. “Lag length selection for vector error correction models.” 2010. Web. 19 Jan 2021.

Vancouver:

Sharp GD. Lag length selection for vector error correction models. [Internet] [Doctoral dissertation]. Rhodes University; 2010. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10962/d1002808.

Council of Science Editors:

Sharp GD. Lag length selection for vector error correction models. [Doctoral Dissertation]. Rhodes University; 2010. Available from: http://hdl.handle.net/10962/d1002808


Columbia University

12. Cai, Xiaochen. Methods for handling measurement error and sources of variation in functional data models.

Degree: 2015, Columbia University

 The overall theme of this thesis work concerns the problem of handling measurement error and sources of variation in functional data models. The first part… (more)

Subjects/Keywords: Error analysis (Mathematics); Analysis of covariance; Biometry; Statistics

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APA (6th Edition):

Cai, X. (2015). Methods for handling measurement error and sources of variation in functional data models. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8M907CJ

Chicago Manual of Style (16th Edition):

Cai, Xiaochen. “Methods for handling measurement error and sources of variation in functional data models.” 2015. Doctoral Dissertation, Columbia University. Accessed January 19, 2021. https://doi.org/10.7916/D8M907CJ.

MLA Handbook (7th Edition):

Cai, Xiaochen. “Methods for handling measurement error and sources of variation in functional data models.” 2015. Web. 19 Jan 2021.

Vancouver:

Cai X. Methods for handling measurement error and sources of variation in functional data models. [Internet] [Doctoral dissertation]. Columbia University; 2015. [cited 2021 Jan 19]. Available from: https://doi.org/10.7916/D8M907CJ.

Council of Science Editors:

Cai X. Methods for handling measurement error and sources of variation in functional data models. [Doctoral Dissertation]. Columbia University; 2015. Available from: https://doi.org/10.7916/D8M907CJ


Hong Kong University of Science and Technology

13. Lam, Chun Hung. Sensitivity analysis and resampling methods on measurement error.

Degree: 1999, Hong Kong University of Science and Technology

Error in measurement is inevitable in epidemiological study. According to the classical regression model, Y=β0 + β[minute]T where Y represents the response, e.g. the occurrence… (more)

Subjects/Keywords: Error analysis (Mathematics) ; Resampling (Statistics)

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APA (6th Edition):

Lam, C. H. (1999). Sensitivity analysis and resampling methods on measurement error. (Thesis). Hong Kong University of Science and Technology. Retrieved from http://repository.ust.hk/ir/Record/1783.1-5081 ; https://doi.org/10.14711/thesis-b645943 ; http://repository.ust.hk/ir/bitstream/1783.1-5081/1/th_redirect.html

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

Chicago Manual of Style (16th Edition):

Lam, Chun Hung. “Sensitivity analysis and resampling methods on measurement error.” 1999. Thesis, Hong Kong University of Science and Technology. Accessed January 19, 2021. http://repository.ust.hk/ir/Record/1783.1-5081 ; https://doi.org/10.14711/thesis-b645943 ; http://repository.ust.hk/ir/bitstream/1783.1-5081/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Lam, Chun Hung. “Sensitivity analysis and resampling methods on measurement error.” 1999. Web. 19 Jan 2021.

Vancouver:

Lam CH. Sensitivity analysis and resampling methods on measurement error. [Internet] [Thesis]. Hong Kong University of Science and Technology; 1999. [cited 2021 Jan 19]. Available from: http://repository.ust.hk/ir/Record/1783.1-5081 ; https://doi.org/10.14711/thesis-b645943 ; http://repository.ust.hk/ir/bitstream/1783.1-5081/1/th_redirect.html.

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

Council of Science Editors:

Lam CH. Sensitivity analysis and resampling methods on measurement error. [Thesis]. Hong Kong University of Science and Technology; 1999. Available from: http://repository.ust.hk/ir/Record/1783.1-5081 ; https://doi.org/10.14711/thesis-b645943 ; http://repository.ust.hk/ir/bitstream/1783.1-5081/1/th_redirect.html

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


University of Arizona

14. Foiles, Carl Luther, 1935-. Error analysis of correlation estimates .

Degree: 1960, University of Arizona

Subjects/Keywords: Correlation (Statistics); Error analysis (Mathematics)

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APA (6th Edition):

Foiles, Carl Luther, 1. (1960). Error analysis of correlation estimates . (Masters Thesis). University of Arizona. Retrieved from http://hdl.handle.net/10150/319276

Chicago Manual of Style (16th Edition):

Foiles, Carl Luther, 1935-. “Error analysis of correlation estimates .” 1960. Masters Thesis, University of Arizona. Accessed January 19, 2021. http://hdl.handle.net/10150/319276.

MLA Handbook (7th Edition):

Foiles, Carl Luther, 1935-. “Error analysis of correlation estimates .” 1960. Web. 19 Jan 2021.

Vancouver:

Foiles, Carl Luther 1. Error analysis of correlation estimates . [Internet] [Masters thesis]. University of Arizona; 1960. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10150/319276.

Council of Science Editors:

Foiles, Carl Luther 1. Error analysis of correlation estimates . [Masters Thesis]. University of Arizona; 1960. Available from: http://hdl.handle.net/10150/319276


University of South Carolina

15. Li, Xiang. Semiparametric Regression In The Presence Of Measurement Error.

Degree: PhD, Statistics, 2018, University of South Carolina

  The error-in-covariates problem has received great attention among researchers who study semiparametric and nonparametric inference for regression models over the past two decades. Without… (more)

Subjects/Keywords: Statistics and Probability; Semiparametric; Regression; Presence; Measurement; Error

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

APA (6th Edition):

Li, X. (2018). Semiparametric Regression In The Presence Of Measurement Error. (Doctoral Dissertation). University of South Carolina. Retrieved from https://scholarcommons.sc.edu/etd/4937

Chicago Manual of Style (16th Edition):

Li, Xiang. “Semiparametric Regression In The Presence Of Measurement Error.” 2018. Doctoral Dissertation, University of South Carolina. Accessed January 19, 2021. https://scholarcommons.sc.edu/etd/4937.

MLA Handbook (7th Edition):

Li, Xiang. “Semiparametric Regression In The Presence Of Measurement Error.” 2018. Web. 19 Jan 2021.

Vancouver:

Li X. Semiparametric Regression In The Presence Of Measurement Error. [Internet] [Doctoral dissertation]. University of South Carolina; 2018. [cited 2021 Jan 19]. Available from: https://scholarcommons.sc.edu/etd/4937.

Council of Science Editors:

Li X. Semiparametric Regression In The Presence Of Measurement Error. [Doctoral Dissertation]. University of South Carolina; 2018. Available from: https://scholarcommons.sc.edu/etd/4937


The Ohio State University

16. White, Staci A. Quantifying Model Error in Bayesian Parameter Estimation.

Degree: PhD, Statistics, 2015, The Ohio State University

 As technological power increases, statistical models are becoming increasing complex. In a Bayesian analysis, performing parametric inference typically requires exploring the posterior distribution using Markov… (more)

Subjects/Keywords: Statistics; Model Error; Bayesian Estimation; Hierarchical Model; Approximation; Kullback-Leibler; divergence

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APA (6th Edition):

White, S. A. (2015). Quantifying Model Error in Bayesian Parameter Estimation. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1433771825

Chicago Manual of Style (16th Edition):

White, Staci A. “Quantifying Model Error in Bayesian Parameter Estimation.” 2015. Doctoral Dissertation, The Ohio State University. Accessed January 19, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1433771825.

MLA Handbook (7th Edition):

White, Staci A. “Quantifying Model Error in Bayesian Parameter Estimation.” 2015. Web. 19 Jan 2021.

Vancouver:

White SA. Quantifying Model Error in Bayesian Parameter Estimation. [Internet] [Doctoral dissertation]. The Ohio State University; 2015. [cited 2021 Jan 19]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1433771825.

Council of Science Editors:

White SA. Quantifying Model Error in Bayesian Parameter Estimation. [Doctoral Dissertation]. The Ohio State University; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1433771825


Virginia Tech

17. Jinn, Nicole Mee-Hyaang. Toward Error-Statistical Principles of Evidence in Statistical Inference.

Degree: MA, Philosophy, 2014, Virginia Tech

 The context for this research is statistical inference, the process of making predictions or inferences about a population from observation and analyses of a sample.… (more)

Subjects/Keywords: Statistical Inference; Evidential/Inferential Interpretations; Evidence; Sampling distributions; Likelihood Principle; Bayesian methods; Error Statistics; Frequentist methods; Philosophy of Statistics; Statistics Education

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

APA (6th Edition):

Jinn, N. M. (2014). Toward Error-Statistical Principles of Evidence in Statistical Inference. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/48420

Chicago Manual of Style (16th Edition):

Jinn, Nicole Mee-Hyaang. “Toward Error-Statistical Principles of Evidence in Statistical Inference.” 2014. Masters Thesis, Virginia Tech. Accessed January 19, 2021. http://hdl.handle.net/10919/48420.

MLA Handbook (7th Edition):

Jinn, Nicole Mee-Hyaang. “Toward Error-Statistical Principles of Evidence in Statistical Inference.” 2014. Web. 19 Jan 2021.

Vancouver:

Jinn NM. Toward Error-Statistical Principles of Evidence in Statistical Inference. [Internet] [Masters thesis]. Virginia Tech; 2014. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10919/48420.

Council of Science Editors:

Jinn NM. Toward Error-Statistical Principles of Evidence in Statistical Inference. [Masters Thesis]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/48420


Wayne State University

18. Lance, Michael. Approximate Vs. Monte Carlo Critical Values For The Winsorized T-Test.

Degree: PhD, Education Evaluation and Research, 2011, Wayne State University

  Historically, it has been accepted practice for critical values for the Winsorized t test for independent samples to be based on adjusted degrees of… (more)

Subjects/Keywords: robustness; t-test; type I error; type II error; winsorize; Educational Assessment, Evaluation, and Research; Psychology; Statistics and Probability

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APA (6th Edition):

Lance, M. (2011). Approximate Vs. Monte Carlo Critical Values For The Winsorized T-Test. (Doctoral Dissertation). Wayne State University. Retrieved from https://digitalcommons.wayne.edu/oa_dissertations/173

Chicago Manual of Style (16th Edition):

Lance, Michael. “Approximate Vs. Monte Carlo Critical Values For The Winsorized T-Test.” 2011. Doctoral Dissertation, Wayne State University. Accessed January 19, 2021. https://digitalcommons.wayne.edu/oa_dissertations/173.

MLA Handbook (7th Edition):

Lance, Michael. “Approximate Vs. Monte Carlo Critical Values For The Winsorized T-Test.” 2011. Web. 19 Jan 2021.

Vancouver:

Lance M. Approximate Vs. Monte Carlo Critical Values For The Winsorized T-Test. [Internet] [Doctoral dissertation]. Wayne State University; 2011. [cited 2021 Jan 19]. Available from: https://digitalcommons.wayne.edu/oa_dissertations/173.

Council of Science Editors:

Lance M. Approximate Vs. Monte Carlo Critical Values For The Winsorized T-Test. [Doctoral Dissertation]. Wayne State University; 2011. Available from: https://digitalcommons.wayne.edu/oa_dissertations/173


Texas A&M University

19. Gruben, David Christopher. Development of a weighted-average estimator from a maximum-likelihood estimator and an instrumental-variable estimator in a structural model.

Degree: MS, statistics, 2012, Texas A&M University

Subjects/Keywords: statistics.; Major statistics.; Error analysis (Mathematics); Estimation theory.

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APA (6th Edition):

Gruben, D. C. (2012). Development of a weighted-average estimator from a maximum-likelihood estimator and an instrumental-variable estimator in a structural model. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-1987-THESIS-G885

Chicago Manual of Style (16th Edition):

Gruben, David Christopher. “Development of a weighted-average estimator from a maximum-likelihood estimator and an instrumental-variable estimator in a structural model.” 2012. Masters Thesis, Texas A&M University. Accessed January 19, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-1987-THESIS-G885.

MLA Handbook (7th Edition):

Gruben, David Christopher. “Development of a weighted-average estimator from a maximum-likelihood estimator and an instrumental-variable estimator in a structural model.” 2012. Web. 19 Jan 2021.

Vancouver:

Gruben DC. Development of a weighted-average estimator from a maximum-likelihood estimator and an instrumental-variable estimator in a structural model. [Internet] [Masters thesis]. Texas A&M University; 2012. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1987-THESIS-G885.

Council of Science Editors:

Gruben DC. Development of a weighted-average estimator from a maximum-likelihood estimator and an instrumental-variable estimator in a structural model. [Masters Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-1987-THESIS-G885


Virginia Commonwealth University

20. Bosse, Anna L. Comparing the Structural Components Variance Estimator and U-Statistics Variance Estimator When Assessing the Difference Between Correlated AUCs with Finite Samples.

Degree: MS, Biostatistics, 2017, Virginia Commonwealth University

  Introduction: The structural components variance estimator proposed by DeLong et al. (1988) is a popular approach used when comparing two correlated AUCs. However, this… (more)

Subjects/Keywords: Correlated AUCs; ROC curves; U-statistics; Structural Components; Power; Type 1 Error; Applied Statistics; Biostatistics; Statistical Methodology

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APA (6th Edition):

Bosse, A. L. (2017). Comparing the Structural Components Variance Estimator and U-Statistics Variance Estimator When Assessing the Difference Between Correlated AUCs with Finite Samples. (Thesis). Virginia Commonwealth University. Retrieved from https://doi.org/10.25772/1XFG-8233 ; https://scholarscompass.vcu.edu/etd/5194

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):

Bosse, Anna L. “Comparing the Structural Components Variance Estimator and U-Statistics Variance Estimator When Assessing the Difference Between Correlated AUCs with Finite Samples.” 2017. Thesis, Virginia Commonwealth University. Accessed January 19, 2021. https://doi.org/10.25772/1XFG-8233 ; https://scholarscompass.vcu.edu/etd/5194.

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

MLA Handbook (7th Edition):

Bosse, Anna L. “Comparing the Structural Components Variance Estimator and U-Statistics Variance Estimator When Assessing the Difference Between Correlated AUCs with Finite Samples.” 2017. Web. 19 Jan 2021.

Vancouver:

Bosse AL. Comparing the Structural Components Variance Estimator and U-Statistics Variance Estimator When Assessing the Difference Between Correlated AUCs with Finite Samples. [Internet] [Thesis]. Virginia Commonwealth University; 2017. [cited 2021 Jan 19]. Available from: https://doi.org/10.25772/1XFG-8233 ; https://scholarscompass.vcu.edu/etd/5194.

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

Council of Science Editors:

Bosse AL. Comparing the Structural Components Variance Estimator and U-Statistics Variance Estimator When Assessing the Difference Between Correlated AUCs with Finite Samples. [Thesis]. Virginia Commonwealth University; 2017. Available from: https://doi.org/10.25772/1XFG-8233 ; https://scholarscompass.vcu.edu/etd/5194

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


University of Washington

21. Wheldon, Mark Christopher. Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data.

Degree: PhD, 2013, University of Washington

 Current methods for reconstructing human populations of the past by age and sex are deterministic or do not formally account for measurement error. I propose… (more)

Subjects/Keywords: Bayesian hierarchical model; Cohort component model; International migration; Measurement error; Sex ratio at birth; Vital rate; Statistics; Demography; statistics

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

APA (6th Edition):

Wheldon, M. C. (2013). Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/22813

Chicago Manual of Style (16th Edition):

Wheldon, Mark Christopher. “Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data.” 2013. Doctoral Dissertation, University of Washington. Accessed January 19, 2021. http://hdl.handle.net/1773/22813.

MLA Handbook (7th Edition):

Wheldon, Mark Christopher. “Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data.” 2013. Web. 19 Jan 2021.

Vancouver:

Wheldon MC. Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data. [Internet] [Doctoral dissertation]. University of Washington; 2013. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1773/22813.

Council of Science Editors:

Wheldon MC. Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data. [Doctoral Dissertation]. University of Washington; 2013. Available from: http://hdl.handle.net/1773/22813


Utah State University

22. Saunders, Garrett. Family-Wise Error Rate Control in Quantitative Trait Loci (QTL) Mapping and Gene Ontology Graphs with Remarks on Family Selection.

Degree: PhD, Mathematics and Statistics, 2014, Utah State University

  The main aim of this dissertation is to meet real needs of practitioners in multiple hypothesis testing. The issue of multiplicity has become a… (more)

Subjects/Keywords: Error; Rate; Control; Quatitative; Mapping; Ontology; Family; Selection; Applied Statistics; Physical Sciences and Mathematics; Statistics and Probability

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APA (6th Edition):

Saunders, G. (2014). Family-Wise Error Rate Control in Quantitative Trait Loci (QTL) Mapping and Gene Ontology Graphs with Remarks on Family Selection. (Doctoral Dissertation). Utah State University. Retrieved from https://digitalcommons.usu.edu/etd/2164

Chicago Manual of Style (16th Edition):

Saunders, Garrett. “Family-Wise Error Rate Control in Quantitative Trait Loci (QTL) Mapping and Gene Ontology Graphs with Remarks on Family Selection.” 2014. Doctoral Dissertation, Utah State University. Accessed January 19, 2021. https://digitalcommons.usu.edu/etd/2164.

MLA Handbook (7th Edition):

Saunders, Garrett. “Family-Wise Error Rate Control in Quantitative Trait Loci (QTL) Mapping and Gene Ontology Graphs with Remarks on Family Selection.” 2014. Web. 19 Jan 2021.

Vancouver:

Saunders G. Family-Wise Error Rate Control in Quantitative Trait Loci (QTL) Mapping and Gene Ontology Graphs with Remarks on Family Selection. [Internet] [Doctoral dissertation]. Utah State University; 2014. [cited 2021 Jan 19]. Available from: https://digitalcommons.usu.edu/etd/2164.

Council of Science Editors:

Saunders G. Family-Wise Error Rate Control in Quantitative Trait Loci (QTL) Mapping and Gene Ontology Graphs with Remarks on Family Selection. [Doctoral Dissertation]. Utah State University; 2014. Available from: https://digitalcommons.usu.edu/etd/2164


UCLA

23. Sosa, Luis Antonio. An Overview of Non-Linear Kernel Functions for Solving the Human Face Recognition Problem.

Degree: Statistics, 2016, UCLA

 Principal Component Analysis has been extensively used in the computer vision field as a method of capturing orthogonal axes of large variability in high-dimensional data… (more)

Subjects/Keywords: Statistics; Computer science; Eigenface; Face Recognition; Kernel; Principal Component Analysis PCA; Reconstruction Error; Unsupervised Learning

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APA (6th Edition):

Sosa, L. A. (2016). An Overview of Non-Linear Kernel Functions for Solving the Human Face Recognition Problem. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/9cm2x3jq

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):

Sosa, Luis Antonio. “An Overview of Non-Linear Kernel Functions for Solving the Human Face Recognition Problem.” 2016. Thesis, UCLA. Accessed January 19, 2021. http://www.escholarship.org/uc/item/9cm2x3jq.

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

MLA Handbook (7th Edition):

Sosa, Luis Antonio. “An Overview of Non-Linear Kernel Functions for Solving the Human Face Recognition Problem.” 2016. Web. 19 Jan 2021.

Vancouver:

Sosa LA. An Overview of Non-Linear Kernel Functions for Solving the Human Face Recognition Problem. [Internet] [Thesis]. UCLA; 2016. [cited 2021 Jan 19]. Available from: http://www.escholarship.org/uc/item/9cm2x3jq.

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

Council of Science Editors:

Sosa LA. An Overview of Non-Linear Kernel Functions for Solving the Human Face Recognition Problem. [Thesis]. UCLA; 2016. Available from: http://www.escholarship.org/uc/item/9cm2x3jq

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


University of California – Berkeley

24. Agarwal, Sameer. Queries with Bounded Errors & Bounded Response Times on Very Large Data.

Degree: Computer Science, 2014, University of California – Berkeley

 Modern data analytics applications typically process massive amounts of data on clusters of tens, hundreds, or thousands of machines to support near-real-time decisions. The quantity… (more)

Subjects/Keywords: Computer science; Statistics; Approximate Query Processing; Bootstrap Diagnostics; Databases; Error Estimation; Sampling

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APA (6th Edition):

Agarwal, S. (2014). Queries with Bounded Errors & Bounded Response Times on Very Large Data. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/58m3199x

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):

Agarwal, Sameer. “Queries with Bounded Errors & Bounded Response Times on Very Large Data.” 2014. Thesis, University of California – Berkeley. Accessed January 19, 2021. http://www.escholarship.org/uc/item/58m3199x.

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

MLA Handbook (7th Edition):

Agarwal, Sameer. “Queries with Bounded Errors & Bounded Response Times on Very Large Data.” 2014. Web. 19 Jan 2021.

Vancouver:

Agarwal S. Queries with Bounded Errors & Bounded Response Times on Very Large Data. [Internet] [Thesis]. University of California – Berkeley; 2014. [cited 2021 Jan 19]. Available from: http://www.escholarship.org/uc/item/58m3199x.

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

Council of Science Editors:

Agarwal S. Queries with Bounded Errors & Bounded Response Times on Very Large Data. [Thesis]. University of California – Berkeley; 2014. Available from: http://www.escholarship.org/uc/item/58m3199x

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

25. Resendes, David Joseph. Statistical Methods for Nonlinear Dynamic Models with Measurement Error Using the Ricker Model.

Degree: PhD, Mathematics, 2011, U of Massachusetts : PhD

  In ecological population management, years of animal counts are fit to nonlinear, dynamic models (e.g. the Ricker model) because the values of the parameters… (more)

Subjects/Keywords: estimating equations; estimation; inference; measurement error; ricker; SIMEX; Mathematics; Statistics and Probability

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APA (6th Edition):

Resendes, D. J. (2011). Statistical Methods for Nonlinear Dynamic Models with Measurement Error Using the Ricker Model. (Doctoral Dissertation). U of Massachusetts : PhD. Retrieved from https://scholarworks.umass.edu/open_access_dissertations/474

Chicago Manual of Style (16th Edition):

Resendes, David Joseph. “Statistical Methods for Nonlinear Dynamic Models with Measurement Error Using the Ricker Model.” 2011. Doctoral Dissertation, U of Massachusetts : PhD. Accessed January 19, 2021. https://scholarworks.umass.edu/open_access_dissertations/474.

MLA Handbook (7th Edition):

Resendes, David Joseph. “Statistical Methods for Nonlinear Dynamic Models with Measurement Error Using the Ricker Model.” 2011. Web. 19 Jan 2021.

Vancouver:

Resendes DJ. Statistical Methods for Nonlinear Dynamic Models with Measurement Error Using the Ricker Model. [Internet] [Doctoral dissertation]. U of Massachusetts : PhD; 2011. [cited 2021 Jan 19]. Available from: https://scholarworks.umass.edu/open_access_dissertations/474.

Council of Science Editors:

Resendes DJ. Statistical Methods for Nonlinear Dynamic Models with Measurement Error Using the Ricker Model. [Doctoral Dissertation]. U of Massachusetts : PhD; 2011. Available from: https://scholarworks.umass.edu/open_access_dissertations/474


Penn State University

26. Ananda, Guruprasad. Decoding the multifactorial nature of mutation rate variation in the human genome using computational and statistical approaches.

Degree: 2012, Penn State University

 Whole genome sequencing and resequencing projects have provided a rich source for studying mutations. There is now substantial evidence indicating regional variation and co-variation of… (more)

Subjects/Keywords: mutation rate variation; tandem repeats; microsatellites; multivariate statistics; NGS error correction; GALAXY project

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APA (6th Edition):

Ananda, G. (2012). Decoding the multifactorial nature of mutation rate variation in the human genome using computational and statistical approaches. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16177

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):

Ananda, Guruprasad. “Decoding the multifactorial nature of mutation rate variation in the human genome using computational and statistical approaches.” 2012. Thesis, Penn State University. Accessed January 19, 2021. https://submit-etda.libraries.psu.edu/catalog/16177.

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

MLA Handbook (7th Edition):

Ananda, Guruprasad. “Decoding the multifactorial nature of mutation rate variation in the human genome using computational and statistical approaches.” 2012. Web. 19 Jan 2021.

Vancouver:

Ananda G. Decoding the multifactorial nature of mutation rate variation in the human genome using computational and statistical approaches. [Internet] [Thesis]. Penn State University; 2012. [cited 2021 Jan 19]. Available from: https://submit-etda.libraries.psu.edu/catalog/16177.

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

Council of Science Editors:

Ananda G. Decoding the multifactorial nature of mutation rate variation in the human genome using computational and statistical approaches. [Thesis]. Penn State University; 2012. Available from: https://submit-etda.libraries.psu.edu/catalog/16177

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

27. Qiu, Siwei. Semileptonic B → D decay at nonzero recoil with 2+1 flavor of improved staggered quarks.

Degree: PhD, Physics & Astronomy, 2013, University of Utah

 The purpose of this thesis is to carry out a precise test of the standard model of particle physics, i.e., the model that describes the… (more)

Subjects/Keywords: Error budget; Lattice; QCD; Statistics

…the kinematic constrain. The blue band is the error band of f+ , while the slashed band is… …the error band of f0… …x28;left) and z 3 (right). The black data points and error bars are for… …error band of f+ , the slashed band is the error band of f0 . When adding experimental data… …we have better control of the error near kinematic point q 2 = 0. So we see smaller error… 

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APA (6th Edition):

Qiu, S. (2013). Semileptonic B → D decay at nonzero recoil with 2+1 flavor of improved staggered quarks. (Doctoral Dissertation). University of Utah. Retrieved from http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2626/rec/2160

Chicago Manual of Style (16th Edition):

Qiu, Siwei. “Semileptonic B → D decay at nonzero recoil with 2+1 flavor of improved staggered quarks.” 2013. Doctoral Dissertation, University of Utah. Accessed January 19, 2021. http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2626/rec/2160.

MLA Handbook (7th Edition):

Qiu, Siwei. “Semileptonic B → D decay at nonzero recoil with 2+1 flavor of improved staggered quarks.” 2013. Web. 19 Jan 2021.

Vancouver:

Qiu S. Semileptonic B → D decay at nonzero recoil with 2+1 flavor of improved staggered quarks. [Internet] [Doctoral dissertation]. University of Utah; 2013. [cited 2021 Jan 19]. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2626/rec/2160.

Council of Science Editors:

Qiu S. Semileptonic B → D decay at nonzero recoil with 2+1 flavor of improved staggered quarks. [Doctoral Dissertation]. University of Utah; 2013. Available from: http://content.lib.utah.edu/cdm/singleitem/collection/etd3/id/2626/rec/2160


University of Washington

28. Arora, Rohit. Variability in Modified Estimators of VaR and ES.

Degree: 2016, University of Washington

 Modified Value-at-Risk (mVaR) and Modified Expected Shortfall (mES) are risk estimators that can be calculated without modelling the distribution of asset returns. These modifided estimators… (more)

Subjects/Keywords: Delta-method; Estimator standard error and efficiency; Modified ES; Modified VaR; Statistics; Finance; applied mathematics

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APA (6th Edition):

Arora, R. (2016). Variability in Modified Estimators of VaR and ES. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/36481

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):

Arora, Rohit. “Variability in Modified Estimators of VaR and ES.” 2016. Thesis, University of Washington. Accessed January 19, 2021. http://hdl.handle.net/1773/36481.

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

MLA Handbook (7th Edition):

Arora, Rohit. “Variability in Modified Estimators of VaR and ES.” 2016. Web. 19 Jan 2021.

Vancouver:

Arora R. Variability in Modified Estimators of VaR and ES. [Internet] [Thesis]. University of Washington; 2016. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1773/36481.

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

Council of Science Editors:

Arora R. Variability in Modified Estimators of VaR and ES. [Thesis]. University of Washington; 2016. Available from: http://hdl.handle.net/1773/36481

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


University of Washington

29. Bergen, Silas. Spatial measurement error methods in air pollution epidemiology.

Degree: PhD, 2014, University of Washington

 Air pollution epidemiology cohort studies often implement a two-stage approach to estimating associations of continuous health outcomes with one or more exposures. An inherent problem… (more)

Subjects/Keywords: air pollution epidemiology; measurement error; spatial statistics; two-stage modeling; Biostatistics; Epidemiology; biostatistics

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APA (6th Edition):

Bergen, S. (2014). Spatial measurement error methods in air pollution epidemiology. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/26011

Chicago Manual of Style (16th Edition):

Bergen, Silas. “Spatial measurement error methods in air pollution epidemiology.” 2014. Doctoral Dissertation, University of Washington. Accessed January 19, 2021. http://hdl.handle.net/1773/26011.

MLA Handbook (7th Edition):

Bergen, Silas. “Spatial measurement error methods in air pollution epidemiology.” 2014. Web. 19 Jan 2021.

Vancouver:

Bergen S. Spatial measurement error methods in air pollution epidemiology. [Internet] [Doctoral dissertation]. University of Washington; 2014. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/1773/26011.

Council of Science Editors:

Bergen S. Spatial measurement error methods in air pollution epidemiology. [Doctoral Dissertation]. University of Washington; 2014. Available from: http://hdl.handle.net/1773/26011


Duke University

30. Akande, Olanrewaju Michael. Bayesian Models for Imputing Missing Data and Editing Erroneous Responses in Surveys .

Degree: 2019, Duke University

  This thesis develops Bayesian methods for handling unit nonresponse, item nonresponse, and erroneous responses in large scale surveys and censuses containing categorical data. I… (more)

Subjects/Keywords: Statistics; Census; Measurement Error; Missing Data; Multiple Imputation; Survey Nonresponse; Survey Weights

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APA (6th Edition):

Akande, O. M. (2019). Bayesian Models for Imputing Missing Data and Editing Erroneous Responses in Surveys . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/18766

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):

Akande, Olanrewaju Michael. “Bayesian Models for Imputing Missing Data and Editing Erroneous Responses in Surveys .” 2019. Thesis, Duke University. Accessed January 19, 2021. http://hdl.handle.net/10161/18766.

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

MLA Handbook (7th Edition):

Akande, Olanrewaju Michael. “Bayesian Models for Imputing Missing Data and Editing Erroneous Responses in Surveys .” 2019. Web. 19 Jan 2021.

Vancouver:

Akande OM. Bayesian Models for Imputing Missing Data and Editing Erroneous Responses in Surveys . [Internet] [Thesis]. Duke University; 2019. [cited 2021 Jan 19]. Available from: http://hdl.handle.net/10161/18766.

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

Council of Science Editors:

Akande OM. Bayesian Models for Imputing Missing Data and Editing Erroneous Responses in Surveys . [Thesis]. Duke University; 2019. Available from: http://hdl.handle.net/10161/18766

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

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