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Dept: Statistics

You searched for subject:(Statistical modeling). Showing records 1 – 30 of 37 total matches.

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Massey University

1. Fitch, Anne Marie. Computationally tractable fitting of graphical models : the cost and benefits of decomposable Bayesian and penalized likelihood approaches.

Degree: PhD, Statistics, 2012, Massey University

 Gaussian graphical models are a useful tool for eliciting information about relationships in data with a multivariate normal distribution. In the rst part of this… (more)

Subjects/Keywords: Graphical modeling (Statistics); Bayesian statistical decision theory

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

APA (6th Edition):

Fitch, A. M. (2012). Computationally tractable fitting of graphical models : the cost and benefits of decomposable Bayesian and penalized likelihood approaches. (Doctoral Dissertation). Massey University. Retrieved from http://hdl.handle.net/10179/3659

Chicago Manual of Style (16th Edition):

Fitch, Anne Marie. “Computationally tractable fitting of graphical models : the cost and benefits of decomposable Bayesian and penalized likelihood approaches.” 2012. Doctoral Dissertation, Massey University. Accessed October 14, 2019. http://hdl.handle.net/10179/3659.

MLA Handbook (7th Edition):

Fitch, Anne Marie. “Computationally tractable fitting of graphical models : the cost and benefits of decomposable Bayesian and penalized likelihood approaches.” 2012. Web. 14 Oct 2019.

Vancouver:

Fitch AM. Computationally tractable fitting of graphical models : the cost and benefits of decomposable Bayesian and penalized likelihood approaches. [Internet] [Doctoral dissertation]. Massey University; 2012. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/10179/3659.

Council of Science Editors:

Fitch AM. Computationally tractable fitting of graphical models : the cost and benefits of decomposable Bayesian and penalized likelihood approaches. [Doctoral Dissertation]. Massey University; 2012. Available from: http://hdl.handle.net/10179/3659


University of Texas – Austin

2. You, Xinqi. A hybrid reduced approach to handle missing values in type 2 diabetes prediction.

Degree: MSin Statistics, Statistics, 2016, University of Texas – Austin

 Diabetes gains more attention among medical institutions and health care organizations as the increasing trend of diabetes around the world. In the United States, 29.1… (more)

Subjects/Keywords: Statistics; Missing value; Data mining; Machine learning; Predictive modeling; Statistical modeling

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APA (6th Edition):

You, X. (2016). A hybrid reduced approach to handle missing values in type 2 diabetes prediction. (Masters Thesis). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/2744

Chicago Manual of Style (16th Edition):

You, Xinqi. “A hybrid reduced approach to handle missing values in type 2 diabetes prediction.” 2016. Masters Thesis, University of Texas – Austin. Accessed October 14, 2019. http://dx.doi.org/10.26153/tsw/2744.

MLA Handbook (7th Edition):

You, Xinqi. “A hybrid reduced approach to handle missing values in type 2 diabetes prediction.” 2016. Web. 14 Oct 2019.

Vancouver:

You X. A hybrid reduced approach to handle missing values in type 2 diabetes prediction. [Internet] [Masters thesis]. University of Texas – Austin; 2016. [cited 2019 Oct 14]. Available from: http://dx.doi.org/10.26153/tsw/2744.

Council of Science Editors:

You X. A hybrid reduced approach to handle missing values in type 2 diabetes prediction. [Masters Thesis]. University of Texas – Austin; 2016. Available from: http://dx.doi.org/10.26153/tsw/2744

3. Sanal, T S. Derivation of a statistical model for predicting poor control of diabetes mellitus.

Degree: Statistics, 2013, Manipal University

This study was conducted to identify the factors associated with poor control of diabetes and to derive a statistical model for predicting poor control of… (more)

Subjects/Keywords: Statistics; Statistical modeling; Perception; Meta- analysis; Poor control of diabetes

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APA (6th Edition):

Sanal, T. S. (2013). Derivation of a statistical model for predicting poor control of diabetes mellitus. (Thesis). Manipal University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/12254

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):

Sanal, T S. “Derivation of a statistical model for predicting poor control of diabetes mellitus.” 2013. Thesis, Manipal University. Accessed October 14, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/12254.

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

MLA Handbook (7th Edition):

Sanal, T S. “Derivation of a statistical model for predicting poor control of diabetes mellitus.” 2013. Web. 14 Oct 2019.

Vancouver:

Sanal TS. Derivation of a statistical model for predicting poor control of diabetes mellitus. [Internet] [Thesis]. Manipal University; 2013. [cited 2019 Oct 14]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/12254.

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

Council of Science Editors:

Sanal TS. Derivation of a statistical model for predicting poor control of diabetes mellitus. [Thesis]. Manipal University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/12254

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


The Ohio State University

4. Wang, Tao. Statistical design and analysis of microarray experiments.

Degree: PhD, Statistics, 2005, The Ohio State University

 Microarray, a bio-technology that allows monitoring of gene expressions for thousands of genes simultaneously, has revolutionized biological and genomic research and holds promising potentials in… (more)

Subjects/Keywords: Statistics; microarray; gene expression; statistical analysis; modeling; statistical design

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APA (6th Edition):

Wang, T. (2005). Statistical design and analysis of microarray experiments. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1117201363

Chicago Manual of Style (16th Edition):

Wang, Tao. “Statistical design and analysis of microarray experiments.” 2005. Doctoral Dissertation, The Ohio State University. Accessed October 14, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1117201363.

MLA Handbook (7th Edition):

Wang, Tao. “Statistical design and analysis of microarray experiments.” 2005. Web. 14 Oct 2019.

Vancouver:

Wang T. Statistical design and analysis of microarray experiments. [Internet] [Doctoral dissertation]. The Ohio State University; 2005. [cited 2019 Oct 14]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1117201363.

Council of Science Editors:

Wang T. Statistical design and analysis of microarray experiments. [Doctoral Dissertation]. The Ohio State University; 2005. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1117201363


University of Florida

5. Xiang, Ruoxuan. Consistency of High Dimensional Bayesian Models.

Degree: PhD, Statistics, 2016, University of Florida

 In the first project, we examine Bayes factor consistency in the context of Bayesian variable selection for normal linear regression models. We take a hierarchical… (more)

Subjects/Keywords: Approximation; Bayes theorem; Covariance; Matrices; Modeling; Parametric models; Statistical estimation; Statistical models; Statistics; Vertices; bayesian  – consistency

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APA (6th Edition):

Xiang, R. (2016). Consistency of High Dimensional Bayesian Models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0050143

Chicago Manual of Style (16th Edition):

Xiang, Ruoxuan. “Consistency of High Dimensional Bayesian Models.” 2016. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0050143.

MLA Handbook (7th Edition):

Xiang, Ruoxuan. “Consistency of High Dimensional Bayesian Models.” 2016. Web. 14 Oct 2019.

Vancouver:

Xiang R. Consistency of High Dimensional Bayesian Models. [Internet] [Doctoral dissertation]. University of Florida; 2016. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0050143.

Council of Science Editors:

Xiang R. Consistency of High Dimensional Bayesian Models. [Doctoral Dissertation]. University of Florida; 2016. Available from: http://ufdc.ufl.edu/UFE0050143


University of Tennessee – Knoxville

6. Zeng, Yan. A Study of Missing Data Imputation and Predictive Modeling of Strength Properties of Wood Composites.

Degree: MS, Statistics, 2011, University of Tennessee – Knoxville

  Problem: Real-time process and destructive test data were collected from a wood composite manufacturer in the U.S. to develop real-time predictive models of two… (more)

Subjects/Keywords: missing data imputation; predictive modeling; partial least squares regression; LASSO; Adaptive LASSO; BART; Applied Statistics; Statistical Methodology; Statistical Models

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APA (6th Edition):

Zeng, Y. (2011). A Study of Missing Data Imputation and Predictive Modeling of Strength Properties of Wood Composites. (Thesis). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_gradthes/1041

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):

Zeng, Yan. “A Study of Missing Data Imputation and Predictive Modeling of Strength Properties of Wood Composites.” 2011. Thesis, University of Tennessee – Knoxville. Accessed October 14, 2019. https://trace.tennessee.edu/utk_gradthes/1041.

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

MLA Handbook (7th Edition):

Zeng, Yan. “A Study of Missing Data Imputation and Predictive Modeling of Strength Properties of Wood Composites.” 2011. Web. 14 Oct 2019.

Vancouver:

Zeng Y. A Study of Missing Data Imputation and Predictive Modeling of Strength Properties of Wood Composites. [Internet] [Thesis]. University of Tennessee – Knoxville; 2011. [cited 2019 Oct 14]. Available from: https://trace.tennessee.edu/utk_gradthes/1041.

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

Council of Science Editors:

Zeng Y. A Study of Missing Data Imputation and Predictive Modeling of Strength Properties of Wood Composites. [Thesis]. University of Tennessee – Knoxville; 2011. Available from: https://trace.tennessee.edu/utk_gradthes/1041

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


University of Florida

7. Pal, Subhadip. Development and Analysis of New Markov Chain Monte Carlo (MCMC) Algorithms.

Degree: PhD, Statistics, 2015, University of Florida

 Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing in the last two decades. MCMC methods have enabled the development and use of intricate… (more)

Subjects/Keywords: Autocorrelation; Ergodic theory; Markov chains; Matrices; Modeling; Regression analysis; Sandwiches; Statistical discrepancies; Statistical models; Statistics; envelope  – geometricergodicity  – mcmc

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APA (6th Edition):

Pal, S. (2015). Development and Analysis of New Markov Chain Monte Carlo (MCMC) Algorithms. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049047

Chicago Manual of Style (16th Edition):

Pal, Subhadip. “Development and Analysis of New Markov Chain Monte Carlo (MCMC) Algorithms.” 2015. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0049047.

MLA Handbook (7th Edition):

Pal, Subhadip. “Development and Analysis of New Markov Chain Monte Carlo (MCMC) Algorithms.” 2015. Web. 14 Oct 2019.

Vancouver:

Pal S. Development and Analysis of New Markov Chain Monte Carlo (MCMC) Algorithms. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0049047.

Council of Science Editors:

Pal S. Development and Analysis of New Markov Chain Monte Carlo (MCMC) Algorithms. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049047


University of Florida

8. Kim, Chan Min. Bayesian Methods for Inference on the Causal Effects of Mediation.

Degree: PhD, Statistics, 2013, University of Florida

 This thesis is motivated by the challenges in analyzing effects of an intervention and mediators on a target outcome, which is called mediation analysis. Typically,… (more)

Subjects/Keywords: Dynamic modeling; Inference; Nondestructive testing; Parametric models; Sensitivity analysis; Statistical discrepancies; Statistical models; Statistics; Tours; Tracheoesophageal fistula; bayesian  – causal  – mediation

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APA (6th Edition):

Kim, C. M. (2013). Bayesian Methods for Inference on the Causal Effects of Mediation. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045730

Chicago Manual of Style (16th Edition):

Kim, Chan Min. “Bayesian Methods for Inference on the Causal Effects of Mediation.” 2013. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0045730.

MLA Handbook (7th Edition):

Kim, Chan Min. “Bayesian Methods for Inference on the Causal Effects of Mediation.” 2013. Web. 14 Oct 2019.

Vancouver:

Kim CM. Bayesian Methods for Inference on the Causal Effects of Mediation. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0045730.

Council of Science Editors:

Kim CM. Bayesian Methods for Inference on the Causal Effects of Mediation. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045730


The Ohio State University

9. Brynjarsdóttir, Jenný. Dimension Reduced Modeling of Spatio-Temporal Processes with Applications to Statistical Downscaling.

Degree: PhD, Statistics, 2011, The Ohio State University

  The field of spatial and spatio-temporal statistics is increasingly faced with the challenge of very large datasets. Examples include data obtained from remote sensing… (more)

Subjects/Keywords: Statistics; Dimension reduction; spatio-temporal modeling; Bayesian hierarchical model; data-dependent basis vectors; statistical downscaling

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APA (6th Edition):

Brynjarsdóttir, J. (2011). Dimension Reduced Modeling of Spatio-Temporal Processes with Applications to Statistical Downscaling. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1312935520

Chicago Manual of Style (16th Edition):

Brynjarsdóttir, Jenný. “Dimension Reduced Modeling of Spatio-Temporal Processes with Applications to Statistical Downscaling.” 2011. Doctoral Dissertation, The Ohio State University. Accessed October 14, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1312935520.

MLA Handbook (7th Edition):

Brynjarsdóttir, Jenný. “Dimension Reduced Modeling of Spatio-Temporal Processes with Applications to Statistical Downscaling.” 2011. Web. 14 Oct 2019.

Vancouver:

Brynjarsdóttir J. Dimension Reduced Modeling of Spatio-Temporal Processes with Applications to Statistical Downscaling. [Internet] [Doctoral dissertation]. The Ohio State University; 2011. [cited 2019 Oct 14]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1312935520.

Council of Science Editors:

Brynjarsdóttir J. Dimension Reduced Modeling of Spatio-Temporal Processes with Applications to Statistical Downscaling. [Doctoral Dissertation]. The Ohio State University; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1312935520


Mahatma Gandhi University

10. Mathew, Aleyamma. Statistical modeling and projections for breast and reproductive tract cancers in Kerala;.

Degree: Statistics, 2014, Mahatma Gandhi University

newline

Bibliography in each chapters, Appendices p. 140-59, Index p. 160

Advisors/Committee Members: Jose, K K.

Subjects/Keywords: Breasts; Kerala; Projections; Reproductive tract cancer; Statistical modeling

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APA (6th Edition):

Mathew, A. (2014). Statistical modeling and projections for breast and reproductive tract cancers in Kerala;. (Thesis). Mahatma Gandhi University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/25780

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):

Mathew, Aleyamma. “Statistical modeling and projections for breast and reproductive tract cancers in Kerala;.” 2014. Thesis, Mahatma Gandhi University. Accessed October 14, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/25780.

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

MLA Handbook (7th Edition):

Mathew, Aleyamma. “Statistical modeling and projections for breast and reproductive tract cancers in Kerala;.” 2014. Web. 14 Oct 2019.

Vancouver:

Mathew A. Statistical modeling and projections for breast and reproductive tract cancers in Kerala;. [Internet] [Thesis]. Mahatma Gandhi University; 2014. [cited 2019 Oct 14]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/25780.

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

Council of Science Editors:

Mathew A. Statistical modeling and projections for breast and reproductive tract cancers in Kerala;. [Thesis]. Mahatma Gandhi University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/25780

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

11. Hewitt, Joshua. Statistical modeling and computing for climate data.

Degree: PhD, Statistics, 2019, Colorado State University

 The motivation for this thesis is to provide improved statistical models and approaches to statistical computing for analyzing climate patterns over short and long distances.… (more)

Subjects/Keywords: Climate; Statistical computing; Hierarchical modeling; Bayesian statistics

…uncertainty, it can be difficult to adapt statistical modeling practices to climate processes… …precipitation. Accordingly, the statistical modeling of spatially-referenced extreme values has been… …models for modeling teleconnections Introduction… …this thesis is to provide improved statistical models and approaches to statistical computing… …x29;. As estimation of statistical models for climate data is computationally expensive, I… 

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APA (6th Edition):

Hewitt, J. (2019). Statistical modeling and computing for climate data. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/195408

Chicago Manual of Style (16th Edition):

Hewitt, Joshua. “Statistical modeling and computing for climate data.” 2019. Doctoral Dissertation, Colorado State University. Accessed October 14, 2019. http://hdl.handle.net/10217/195408.

MLA Handbook (7th Edition):

Hewitt, Joshua. “Statistical modeling and computing for climate data.” 2019. Web. 14 Oct 2019.

Vancouver:

Hewitt J. Statistical modeling and computing for climate data. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2019 Oct 14]. Available from: http://hdl.handle.net/10217/195408.

Council of Science Editors:

Hewitt J. Statistical modeling and computing for climate data. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195408


University of Florida

12. Chatterjee, Arkendu S. Bayesian Model Selection and Fit for Incomplete Longitudinal Data.

Degree: PhD, Statistics, 2013, University of Florida

 In this dissertation, we explore Bayesian approaches for model selection and fit in models for incomplete  longitudinal based on the posterior predictive distribution. We first explore… (more)

Subjects/Keywords: Data models; Longitudinal data; Missing data; Modeling; Parametric models; Predictive modeling; Sample size; School dropouts; Statistical models; Statistics; bayes  – incomplete  – longitudinal  – model  – posterior  – predictive  – selection

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APA (6th Edition):

Chatterjee, A. S. (2013). Bayesian Model Selection and Fit for Incomplete Longitudinal Data. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0045176

Chicago Manual of Style (16th Edition):

Chatterjee, Arkendu S. “Bayesian Model Selection and Fit for Incomplete Longitudinal Data.” 2013. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0045176.

MLA Handbook (7th Edition):

Chatterjee, Arkendu S. “Bayesian Model Selection and Fit for Incomplete Longitudinal Data.” 2013. Web. 14 Oct 2019.

Vancouver:

Chatterjee AS. Bayesian Model Selection and Fit for Incomplete Longitudinal Data. [Internet] [Doctoral dissertation]. University of Florida; 2013. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0045176.

Council of Science Editors:

Chatterjee AS. Bayesian Model Selection and Fit for Incomplete Longitudinal Data. [Doctoral Dissertation]. University of Florida; 2013. Available from: http://ufdc.ufl.edu/UFE0045176


University of Florida

13. Bhadra, Dhiman. Bayesian Semiparametric Regression and Related Applications.

Degree: PhD, Statistics, 2010, University of Florida

 Case-Control studies and small area estimation are two distinct areas of modern Statistics. The former deals with the comparison of diseased and healthy subjects with… (more)

Subjects/Keywords: Case control studies; Diseases; Income estimates; Median income; Modeling; School dropouts; Semiparametric modeling; Statistical estimation; Statistics; Trajectories; bayesian, case, current, mcmc, odds, penalized, random, semiparametric

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APA (6th Edition):

Bhadra, D. (2010). Bayesian Semiparametric Regression and Related Applications. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0041832

Chicago Manual of Style (16th Edition):

Bhadra, Dhiman. “Bayesian Semiparametric Regression and Related Applications.” 2010. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0041832.

MLA Handbook (7th Edition):

Bhadra, Dhiman. “Bayesian Semiparametric Regression and Related Applications.” 2010. Web. 14 Oct 2019.

Vancouver:

Bhadra D. Bayesian Semiparametric Regression and Related Applications. [Internet] [Doctoral dissertation]. University of Florida; 2010. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0041832.

Council of Science Editors:

Bhadra D. Bayesian Semiparametric Regression and Related Applications. [Doctoral Dissertation]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0041832


University of Florida

14. Hartless, Glen Lawson, 1971-. Local assessment of perturbations.

Degree: PhD, Statistics, 2000, University of Florida

Subjects/Keywords: Acceleration; Curvature; Inference; Linear regression; Matrices; Modeling; Statistical discrepancies; Statistical estimation; Statistical models; Statistics

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APA (6th Edition):

Hartless, Glen Lawson, 1. (2000). Local assessment of perturbations. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00020429

Chicago Manual of Style (16th Edition):

Hartless, Glen Lawson, 1971-. “Local assessment of perturbations.” 2000. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00020429.

MLA Handbook (7th Edition):

Hartless, Glen Lawson, 1971-. “Local assessment of perturbations.” 2000. Web. 14 Oct 2019.

Vancouver:

Hartless, Glen Lawson 1. Local assessment of perturbations. [Internet] [Doctoral dissertation]. University of Florida; 2000. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00020429.

Council of Science Editors:

Hartless, Glen Lawson 1. Local assessment of perturbations. [Doctoral Dissertation]. University of Florida; 2000. Available from: http://ufdc.ufl.edu/AA00020429


University of Florida

15. Lee, Juneyoung, 1963-. Design comparisons and modeling aspects for unbalanced random models.

Degree: PhD, Statistics, 1999, University of Florida

Subjects/Keywords: Confidence interval; Contour lines; Estimation methods; Modeling; Probabilities; Quantiles; Statistical discrepancies; Statistical estimation; Statistical models; Statistics

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APA (6th Edition):

Lee, Juneyoung, 1. (1999). Design comparisons and modeling aspects for unbalanced random models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00038853

Chicago Manual of Style (16th Edition):

Lee, Juneyoung, 1963-. “Design comparisons and modeling aspects for unbalanced random models.” 1999. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00038853.

MLA Handbook (7th Edition):

Lee, Juneyoung, 1963-. “Design comparisons and modeling aspects for unbalanced random models.” 1999. Web. 14 Oct 2019.

Vancouver:

Lee, Juneyoung 1. Design comparisons and modeling aspects for unbalanced random models. [Internet] [Doctoral dissertation]. University of Florida; 1999. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00038853.

Council of Science Editors:

Lee, Juneyoung 1. Design comparisons and modeling aspects for unbalanced random models. [Doctoral Dissertation]. University of Florida; 1999. Available from: http://ufdc.ufl.edu/AA00038853


University of Florida

16. Wang, Chenguang. Bayesian Nonparametric and Semi-Parametric Methods for Incomplete Longitudinal Data.

Degree: PhD, Statistics, 2010, University of Florida

 BAYESIAN NONPARAMETRIC AND SEMI-PARAMETRIC METHODS FOR INCOMPLETE LONGITUDINAL DATA We consider inference in randomized longitudinal studies with missing data that is generated by skipped clinic… (more)

Subjects/Keywords: Biometrics; Data models; Inference; Missing data; Modeling; Parametric models; Placebos; School dropouts; Sensitivity analysis; Statistical models; bayesian, dropout, elicitation, intermittent, longitudinal, missing, nonparametric, shrinkage

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APA (6th Edition):

Wang, C. (2010). Bayesian Nonparametric and Semi-Parametric Methods for Incomplete Longitudinal Data. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0041942

Chicago Manual of Style (16th Edition):

Wang, Chenguang. “Bayesian Nonparametric and Semi-Parametric Methods for Incomplete Longitudinal Data.” 2010. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0041942.

MLA Handbook (7th Edition):

Wang, Chenguang. “Bayesian Nonparametric and Semi-Parametric Methods for Incomplete Longitudinal Data.” 2010. Web. 14 Oct 2019.

Vancouver:

Wang C. Bayesian Nonparametric and Semi-Parametric Methods for Incomplete Longitudinal Data. [Internet] [Doctoral dissertation]. University of Florida; 2010. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0041942.

Council of Science Editors:

Wang C. Bayesian Nonparametric and Semi-Parametric Methods for Incomplete Longitudinal Data. [Doctoral Dissertation]. University of Florida; 2010. Available from: http://ufdc.ufl.edu/UFE0041942


University of Florida

17. Savenkov, Oleksandr. Novel Methods for Time Series Data in Clinical Studies.

Degree: PhD, Statistics, 2012, University of Florida

 Single subject or n-of-1 research designs have been widely used to evaluate treatment interventions. Many statistical procedures, such as: split-middle trend lines, regression trend line,… (more)

Subjects/Keywords: Autocorrelation; Autoregressive moving average; Data lines; False positive errors; Modeling; Permutation tests; Statistical models; Statistics; Time series; Time series models; design  – series  – single  – subject  – time

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

APA (6th Edition):

Savenkov, O. (2012). Novel Methods for Time Series Data in Clinical Studies. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0044593

Chicago Manual of Style (16th Edition):

Savenkov, Oleksandr. “Novel Methods for Time Series Data in Clinical Studies.” 2012. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0044593.

MLA Handbook (7th Edition):

Savenkov, Oleksandr. “Novel Methods for Time Series Data in Clinical Studies.” 2012. Web. 14 Oct 2019.

Vancouver:

Savenkov O. Novel Methods for Time Series Data in Clinical Studies. [Internet] [Doctoral dissertation]. University of Florida; 2012. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0044593.

Council of Science Editors:

Savenkov O. Novel Methods for Time Series Data in Clinical Studies. [Doctoral Dissertation]. University of Florida; 2012. Available from: http://ufdc.ufl.edu/UFE0044593


University of Florida

18. Ozrazgat Baslanti,T. The Stereotype Model and the Existence of Maximum Likelihood Estimates in Categorical Regression Models.

Degree: PhD, Statistics, 2011, University of Florida

 In this dissertation, we focus on two main topics: the stereotype model and the existence of maximum likelihood estimates in categorical regression models. Despite the… (more)

Subjects/Keywords: Confidence interval; Logistics; Maximum likelihood estimates; Maximum likelihood estimations; Modeling; Parametric models; Ratio test; Statistical models; Statistics; Stereotypes; categorical  – estimates  – existence  – likelihood  – logistic  – maximum  – mle  – model  – ordinal  – partial  – stereotype

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APA (6th Edition):

Baslanti,T, O. (2011). The Stereotype Model and the Existence of Maximum Likelihood Estimates in Categorical Regression Models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043178

Chicago Manual of Style (16th Edition):

Baslanti,T, Ozrazgat. “The Stereotype Model and the Existence of Maximum Likelihood Estimates in Categorical Regression Models.” 2011. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0043178.

MLA Handbook (7th Edition):

Baslanti,T, Ozrazgat. “The Stereotype Model and the Existence of Maximum Likelihood Estimates in Categorical Regression Models.” 2011. Web. 14 Oct 2019.

Vancouver:

Baslanti,T O. The Stereotype Model and the Existence of Maximum Likelihood Estimates in Categorical Regression Models. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0043178.

Council of Science Editors:

Baslanti,T O. The Stereotype Model and the Existence of Maximum Likelihood Estimates in Categorical Regression Models. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043178


The Ohio State University

19. Johannesson, Gardar. Multi-Resolution Statistical Modeling in Space and Time With Application to Remote Sensing of the Environment.

Degree: PhD, Statistics, 2003, The Ohio State University

 Analyzing massive spatial and space-time environmental datasets can be demanding. A central example used in this dissertation is the analysis of Total Column Ozone (TCO)… (more)

Subjects/Keywords: Total Column Ozone (TCO); massive data; statistical multi-resolution modeling; variance-covariance estimation; physics-based dynamic statistical models

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APA (6th Edition):

Johannesson, G. (2003). Multi-Resolution Statistical Modeling in Space and Time With Application to Remote Sensing of the Environment. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1051282014

Chicago Manual of Style (16th Edition):

Johannesson, Gardar. “Multi-Resolution Statistical Modeling in Space and Time With Application to Remote Sensing of the Environment.” 2003. Doctoral Dissertation, The Ohio State University. Accessed October 14, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1051282014.

MLA Handbook (7th Edition):

Johannesson, Gardar. “Multi-Resolution Statistical Modeling in Space and Time With Application to Remote Sensing of the Environment.” 2003. Web. 14 Oct 2019.

Vancouver:

Johannesson G. Multi-Resolution Statistical Modeling in Space and Time With Application to Remote Sensing of the Environment. [Internet] [Doctoral dissertation]. The Ohio State University; 2003. [cited 2019 Oct 14]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1051282014.

Council of Science Editors:

Johannesson G. Multi-Resolution Statistical Modeling in Space and Time With Application to Remote Sensing of the Environment. [Doctoral Dissertation]. The Ohio State University; 2003. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1051282014


University of Florida

20. Gueorguieva, Ralitza, 1971-. Models for repeated measures of a multivariate response.

Degree: PhD, Statistics, 1999, University of Florida

Subjects/Keywords: Approximation; Gaussian quadratures; Maximum likelihood estimations; Modeling; Sample size; Simulations; Standard error; Statistical discrepancies; Statistical models; Statistics

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APA (6th Edition):

Gueorguieva, Ralitza, 1. (1999). Models for repeated measures of a multivariate response. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00020402

Chicago Manual of Style (16th Edition):

Gueorguieva, Ralitza, 1971-. “Models for repeated measures of a multivariate response.” 1999. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00020402.

MLA Handbook (7th Edition):

Gueorguieva, Ralitza, 1971-. “Models for repeated measures of a multivariate response.” 1999. Web. 14 Oct 2019.

Vancouver:

Gueorguieva, Ralitza 1. Models for repeated measures of a multivariate response. [Internet] [Doctoral dissertation]. University of Florida; 1999. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00020402.

Council of Science Editors:

Gueorguieva, Ralitza 1. Models for repeated measures of a multivariate response. [Doctoral Dissertation]. University of Florida; 1999. Available from: http://ufdc.ufl.edu/AA00020402


University of Florida

21. Jank, Wolfgang S., 1970-. Stochastic estimation methods in general hierarchical models.

Degree: PhD, Statistics, 2001, University of Florida

Subjects/Keywords: Approximation; Estimation methods; Maximum likelihood estimations; Modeling; Multilevel models; Sample size; Simulations; Statistical discrepancies; Statistical models; Statistics

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APA (6th Edition):

Jank, Wolfgang S., 1. (2001). Stochastic estimation methods in general hierarchical models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00039135

Chicago Manual of Style (16th Edition):

Jank, Wolfgang S., 1970-. “Stochastic estimation methods in general hierarchical models.” 2001. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00039135.

MLA Handbook (7th Edition):

Jank, Wolfgang S., 1970-. “Stochastic estimation methods in general hierarchical models.” 2001. Web. 14 Oct 2019.

Vancouver:

Jank, Wolfgang S. 1. Stochastic estimation methods in general hierarchical models. [Internet] [Doctoral dissertation]. University of Florida; 2001. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00039135.

Council of Science Editors:

Jank, Wolfgang S. 1. Stochastic estimation methods in general hierarchical models. [Doctoral Dissertation]. University of Florida; 2001. Available from: http://ufdc.ufl.edu/AA00039135


University of Florida

22. Ghosh, Atalanta, 1964-. Bayesian analysis of item response models for binary data.

Degree: PhD, Statistics, 1996, University of Florida

Subjects/Keywords: Bayes estimators; Bayesian analysis; Maximum likelihood estimations; Modeling; Parametric models; Standard error; Statistical estimation; Statistical models; Statistics; Wildlife population estimation

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APA (6th Edition):

Ghosh, Atalanta, 1. (1996). Bayesian analysis of item response models for binary data. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00034598

Chicago Manual of Style (16th Edition):

Ghosh, Atalanta, 1964-. “Bayesian analysis of item response models for binary data.” 1996. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00034598.

MLA Handbook (7th Edition):

Ghosh, Atalanta, 1964-. “Bayesian analysis of item response models for binary data.” 1996. Web. 14 Oct 2019.

Vancouver:

Ghosh, Atalanta 1. Bayesian analysis of item response models for binary data. [Internet] [Doctoral dissertation]. University of Florida; 1996. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00034598.

Council of Science Editors:

Ghosh, Atalanta 1. Bayesian analysis of item response models for binary data. [Doctoral Dissertation]. University of Florida; 1996. Available from: http://ufdc.ufl.edu/AA00034598


University of Florida

23. Coull, Brent Andrew, 1970-. Subject-specific modelling of capture-recapture experiments.

Degree: PhD, Statistics, 1997, University of Florida

Subjects/Keywords: Confidence interval; Modeling; Nonparametric models; Parametric models; Percentiles; Point estimators; Population estimates; Population size; Statistical median; Statistical models

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APA (6th Edition):

Coull, Brent Andrew, 1. (1997). Subject-specific modelling of capture-recapture experiments. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00017652

Chicago Manual of Style (16th Edition):

Coull, Brent Andrew, 1970-. “Subject-specific modelling of capture-recapture experiments.” 1997. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00017652.

MLA Handbook (7th Edition):

Coull, Brent Andrew, 1970-. “Subject-specific modelling of capture-recapture experiments.” 1997. Web. 14 Oct 2019.

Vancouver:

Coull, Brent Andrew 1. Subject-specific modelling of capture-recapture experiments. [Internet] [Doctoral dissertation]. University of Florida; 1997. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00017652.

Council of Science Editors:

Coull, Brent Andrew 1. Subject-specific modelling of capture-recapture experiments. [Doctoral Dissertation]. University of Florida; 1997. Available from: http://ufdc.ufl.edu/AA00017652


University of Florida

24. Wu, Song. A Robust Approach for Genetic Mapping of Complex Traits.

Degree: PhD, Statistics, 2008, University of Florida

 Genetic mapping has proven to be a powerful tool for studying the genetic architecture of complex traits by localizing individual quantitative trait loci (QTLs) that… (more)

Subjects/Keywords: Alleles; Genotypes; Haplotypes; Modeling; Phenotypic traits; Population estimates; Population genetics; Quantitative trait loci; Quantitative traits; Statistical models; functional, haplotype, hardy, integrated, l2e, linkage, qtl, statistical, zygotic

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APA (6th Edition):

Wu, S. (2008). A Robust Approach for Genetic Mapping of Complex Traits. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0022399

Chicago Manual of Style (16th Edition):

Wu, Song. “A Robust Approach for Genetic Mapping of Complex Traits.” 2008. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/UFE0022399.

MLA Handbook (7th Edition):

Wu, Song. “A Robust Approach for Genetic Mapping of Complex Traits.” 2008. Web. 14 Oct 2019.

Vancouver:

Wu S. A Robust Approach for Genetic Mapping of Complex Traits. [Internet] [Doctoral dissertation]. University of Florida; 2008. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/UFE0022399.

Council of Science Editors:

Wu S. A Robust Approach for Genetic Mapping of Complex Traits. [Doctoral Dissertation]. University of Florida; 2008. Available from: http://ufdc.ufl.edu/UFE0022399


University of Florida

25. Min, Yongyi. Modeling data with clumps.

Degree: PhD, Statistics, 2003, University of Florida

Subjects/Keywords: Data models; Datasets; Estimation methods; Medication adherence; Modeling; Nonparametric models; Parametric models; Patient compliance; Statistical models; Statistics

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APA (6th Edition):

Min, Y. (2003). Modeling data with clumps. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00039291

Chicago Manual of Style (16th Edition):

Min, Yongyi. “Modeling data with clumps.” 2003. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00039291.

MLA Handbook (7th Edition):

Min, Yongyi. “Modeling data with clumps.” 2003. Web. 14 Oct 2019.

Vancouver:

Min Y. Modeling data with clumps. [Internet] [Doctoral dissertation]. University of Florida; 2003. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00039291.

Council of Science Editors:

Min Y. Modeling data with clumps. [Doctoral Dissertation]. University of Florida; 2003. Available from: http://ufdc.ufl.edu/AA00039291


University of Florida

26. Tanaka, Yoko, 1962-. A proportional hazards model for informatively censored survival times.

Degree: PhD, Statistics, 1998, University of Florida

Subjects/Keywords: Censored data; Censorship; Confidence interval; Death; Estimators; Martingales; Modeling; Relapse; Reliability functions; Statistical models

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APA (6th Edition):

Tanaka, Yoko, 1. (1998). A proportional hazards model for informatively censored survival times. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00040698

Chicago Manual of Style (16th Edition):

Tanaka, Yoko, 1962-. “A proportional hazards model for informatively censored survival times.” 1998. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00040698.

MLA Handbook (7th Edition):

Tanaka, Yoko, 1962-. “A proportional hazards model for informatively censored survival times.” 1998. Web. 14 Oct 2019.

Vancouver:

Tanaka, Yoko 1. A proportional hazards model for informatively censored survival times. [Internet] [Doctoral dissertation]. University of Florida; 1998. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00040698.

Council of Science Editors:

Tanaka, Yoko 1. A proportional hazards model for informatively censored survival times. [Doctoral Dissertation]. University of Florida; 1998. Available from: http://ufdc.ufl.edu/AA00040698


University of Florida

27. Wang, Chen-Pin, 1970-. Bayesian analysis of competing risks models.

Degree: PhD, Statistics, 1999, University of Florida

Subjects/Keywords: Bayesian analysis; Fisher information; Frequentism; Mathematical independent variables; Modeling; Parametric models; Reliability functions; Statistical models; Statistics; Stochastic models

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APA (6th Edition):

Wang, Chen-Pin, 1. (1999). Bayesian analysis of competing risks models. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00038858

Chicago Manual of Style (16th Edition):

Wang, Chen-Pin, 1970-. “Bayesian analysis of competing risks models.” 1999. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00038858.

MLA Handbook (7th Edition):

Wang, Chen-Pin, 1970-. “Bayesian analysis of competing risks models.” 1999. Web. 14 Oct 2019.

Vancouver:

Wang, Chen-Pin 1. Bayesian analysis of competing risks models. [Internet] [Doctoral dissertation]. University of Florida; 1999. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00038858.

Council of Science Editors:

Wang, Chen-Pin 1. Bayesian analysis of competing risks models. [Doctoral Dissertation]. University of Florida; 1999. Available from: http://ufdc.ufl.edu/AA00038858

28. Wong, Samuel Wing Kwong. Statistical Computation for Problems in Dynamic Systems and Protein Folding.

Degree: PhD, Statistics, 2013, Harvard University

Inference for dynamic systems and conformational sampling for protein folding are two problems motivated by applied data, which pose computational challenges from a statistical perspective.… (more)

Subjects/Keywords: Statistics; dynamic systems; loop modeling; protein structure prediction; sampling methods; statistical computation

statistical thinking, while also giving me the freedom to develop my skills as a researcher. He had… 

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

APA (6th Edition):

Wong, S. W. K. (2013). Statistical Computation for Problems in Dynamic Systems and Protein Folding. (Doctoral Dissertation). Harvard University. Retrieved from http://nrs.harvard.edu/urn-3:HUL.InstRepos:10973930

Chicago Manual of Style (16th Edition):

Wong, Samuel Wing Kwong. “Statistical Computation for Problems in Dynamic Systems and Protein Folding.” 2013. Doctoral Dissertation, Harvard University. Accessed October 14, 2019. http://nrs.harvard.edu/urn-3:HUL.InstRepos:10973930.

MLA Handbook (7th Edition):

Wong, Samuel Wing Kwong. “Statistical Computation for Problems in Dynamic Systems and Protein Folding.” 2013. Web. 14 Oct 2019.

Vancouver:

Wong SWK. Statistical Computation for Problems in Dynamic Systems and Protein Folding. [Internet] [Doctoral dissertation]. Harvard University; 2013. [cited 2019 Oct 14]. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10973930.

Council of Science Editors:

Wong SWK. Statistical Computation for Problems in Dynamic Systems and Protein Folding. [Doctoral Dissertation]. Harvard University; 2013. Available from: http://nrs.harvard.edu/urn-3:HUL.InstRepos:10973930


University of Florida

29. Shiau, Deng-Shan, 1968-. Signal identification and forecasting in nonstationary time series data.

Degree: PhD, Statistics, 2001, University of Florida

Subjects/Keywords: Analytical forecasting; Forecasting models; Forecasting techniques; Modeling; Signals; Statistical forecasts; Sunspots; Time series; Time series forecasting; Time series models

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APA (6th Edition):

Shiau, Deng-Shan, 1. (2001). Signal identification and forecasting in nonstationary time series data. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00040377

Chicago Manual of Style (16th Edition):

Shiau, Deng-Shan, 1968-. “Signal identification and forecasting in nonstationary time series data.” 2001. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00040377.

MLA Handbook (7th Edition):

Shiau, Deng-Shan, 1968-. “Signal identification and forecasting in nonstationary time series data.” 2001. Web. 14 Oct 2019.

Vancouver:

Shiau, Deng-Shan 1. Signal identification and forecasting in nonstationary time series data. [Internet] [Doctoral dissertation]. University of Florida; 2001. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00040377.

Council of Science Editors:

Shiau, Deng-Shan 1. Signal identification and forecasting in nonstationary time series data. [Doctoral Dissertation]. University of Florida; 2001. Available from: http://ufdc.ufl.edu/AA00040377


University of Florida

30. Morrison, Scott P., 1968-. A multiple regression model for angular responses.

Degree: PhD, Statistics, 1995, University of Florida

Subjects/Keywords: Estimation methods; Gaussian distributions; Maximum likelihood estimations; Modeling; Parametric models; Regression analysis; Sample size; Simulations; Statistical models; Statistics

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APA (6th Edition):

Morrison, Scott P., 1. (1995). A multiple regression model for angular responses. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/AA00041117

Chicago Manual of Style (16th Edition):

Morrison, Scott P., 1968-. “A multiple regression model for angular responses.” 1995. Doctoral Dissertation, University of Florida. Accessed October 14, 2019. http://ufdc.ufl.edu/AA00041117.

MLA Handbook (7th Edition):

Morrison, Scott P., 1968-. “A multiple regression model for angular responses.” 1995. Web. 14 Oct 2019.

Vancouver:

Morrison, Scott P. 1. A multiple regression model for angular responses. [Internet] [Doctoral dissertation]. University of Florida; 1995. [cited 2019 Oct 14]. Available from: http://ufdc.ufl.edu/AA00041117.

Council of Science Editors:

Morrison, Scott P. 1. A multiple regression model for angular responses. [Doctoral Dissertation]. University of Florida; 1995. Available from: http://ufdc.ufl.edu/AA00041117

[1] [2]

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