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You searched for subject:(Bayesian Statistics AND Decision Analysis). Showing records 1 – 30 of 242 total matches.

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University of Helsinki

1. Yi, Xinxin. Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation.

Degree: 2015, University of Helsinki

Problem: Helsinki psychotherapy study (HPS) is a quasi-experimental clinical trial, which is designed to compare the effects of different treatments (i.e. psychotherapy and psychoanalysis) on… (more)

Subjects/Keywords: Bayesian Statistics and Decision Analysis

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

APA (6th Edition):

Yi, X. (2015). Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation. (Thesis). University of Helsinki. Retrieved from http://hdl.handle.net/10138/158386

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):

Yi, Xinxin. “Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation.” 2015. Thesis, University of Helsinki. Accessed August 10, 2020. http://hdl.handle.net/10138/158386.

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

MLA Handbook (7th Edition):

Yi, Xinxin. “Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation.” 2015. Web. 10 Aug 2020.

Vancouver:

Yi X. Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation. [Internet] [Thesis]. University of Helsinki; 2015. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10138/158386.

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

Council of Science Editors:

Yi X. Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation. [Thesis]. University of Helsinki; 2015. Available from: http://hdl.handle.net/10138/158386

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


University of Helsinki

2. Huang, Zhiyong. Linear Models with Regularization.

Degree: 2012, University of Helsinki

In this master’s thesis we present two important classes of regularized linear models -regularized least squares regression (LS) and regularized least absolute deviation (LAD). Use… (more)

Subjects/Keywords: Bayesian Statistics and Decision Analysis

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APA (6th Edition):

Huang, Z. (2012). Linear Models with Regularization. (Thesis). University of Helsinki. Retrieved from http://hdl.handle.net/10138/37086

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):

Huang, Zhiyong. “Linear Models with Regularization.” 2012. Thesis, University of Helsinki. Accessed August 10, 2020. http://hdl.handle.net/10138/37086.

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

MLA Handbook (7th Edition):

Huang, Zhiyong. “Linear Models with Regularization.” 2012. Web. 10 Aug 2020.

Vancouver:

Huang Z. Linear Models with Regularization. [Internet] [Thesis]. University of Helsinki; 2012. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10138/37086.

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

Council of Science Editors:

Huang Z. Linear Models with Regularization. [Thesis]. University of Helsinki; 2012. Available from: http://hdl.handle.net/10138/37086

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


University of Helsinki

3. Benner, Christian. Bayesian confirmatory factor analysis for detection of differential gene expression.

Degree: 2013, University of Helsinki

Background. DNA microarrays measure the expression levels of tens of thousands of genes simultaneously. Some differentially expressed genes may be useful as markers for the… (more)

Subjects/Keywords: Bayesian Statistics and Decision Analysis

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APA (6th Edition):

Benner, C. (2013). Bayesian confirmatory factor analysis for detection of differential gene expression. (Thesis). University of Helsinki. Retrieved from http://hdl.handle.net/10138/38495

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):

Benner, Christian. “Bayesian confirmatory factor analysis for detection of differential gene expression.” 2013. Thesis, University of Helsinki. Accessed August 10, 2020. http://hdl.handle.net/10138/38495.

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

MLA Handbook (7th Edition):

Benner, Christian. “Bayesian confirmatory factor analysis for detection of differential gene expression.” 2013. Web. 10 Aug 2020.

Vancouver:

Benner C. Bayesian confirmatory factor analysis for detection of differential gene expression. [Internet] [Thesis]. University of Helsinki; 2013. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10138/38495.

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

Council of Science Editors:

Benner C. Bayesian confirmatory factor analysis for detection of differential gene expression. [Thesis]. University of Helsinki; 2013. Available from: http://hdl.handle.net/10138/38495

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


University of Helsinki

4. Yi, Xinxin. Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation.

Degree: 2016, University of Helsinki

Problem: Helsinki psychotherapy study (HPS) is a quasi-experimental clinical trial, which is designed to compare the effects of different treatments (i.e. psychotherapy and psychoanalysis) on… (more)

Subjects/Keywords: Bayesian Statistics and Decision Analysis

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

APA (6th Edition):

Yi, X. (2016). Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation. (Thesis). University of Helsinki. Retrieved from http://hdl.handle.net/10138/160856

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):

Yi, Xinxin. “Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation.” 2016. Thesis, University of Helsinki. Accessed August 10, 2020. http://hdl.handle.net/10138/160856.

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

MLA Handbook (7th Edition):

Yi, Xinxin. “Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation.” 2016. Web. 10 Aug 2020.

Vancouver:

Yi X. Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation. [Internet] [Thesis]. University of Helsinki; 2016. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10138/160856.

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

Council of Science Editors:

Yi X. Correcting the Effects of Missing Data in Helsinki Psychotherapy Study using Multiple Imputation. [Thesis]. University of Helsinki; 2016. Available from: http://hdl.handle.net/10138/160856

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


Rhodes University

5. Southey, Richard. Bayesian hierarchical modelling with application in spatial epidemiology.

Degree: Faculty of Science, Statistics, 2018, Rhodes University

 Disease mapping and spatial statistics have become an important part of modern day statistics and have increased in popularity as the methods and techniques have… (more)

Subjects/Keywords: Spatial analysis (Statistics); Bayesian statistical decision theory; Medical mapping; Mouth  – Cancer

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APA (6th Edition):

Southey, R. (2018). Bayesian hierarchical modelling with application in spatial epidemiology. (Thesis). Rhodes University. Retrieved from http://hdl.handle.net/10962/59489

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):

Southey, Richard. “Bayesian hierarchical modelling with application in spatial epidemiology.” 2018. Thesis, Rhodes University. Accessed August 10, 2020. http://hdl.handle.net/10962/59489.

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

MLA Handbook (7th Edition):

Southey, Richard. “Bayesian hierarchical modelling with application in spatial epidemiology.” 2018. Web. 10 Aug 2020.

Vancouver:

Southey R. Bayesian hierarchical modelling with application in spatial epidemiology. [Internet] [Thesis]. Rhodes University; 2018. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10962/59489.

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

Council of Science Editors:

Southey R. Bayesian hierarchical modelling with application in spatial epidemiology. [Thesis]. Rhodes University; 2018. Available from: http://hdl.handle.net/10962/59489

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


Florida Atlantic University

6. Abraha, Yonas Kidane. Bayesian approach to an exponential hazard regression model with a change point.

Degree: MS, 2014, Florida Atlantic University

Summary: This thesis contains two parts. The first part derives the Bayesian estimator of the parameters in a piecewise exponential Cox proportional hazard regression model,… (more)

Subjects/Keywords: Bayesian statistical decision theory; Mathematical statistics; Multivariate analysis  – Data processing

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

APA (6th Edition):

Abraha, Y. K. (2014). Bayesian approach to an exponential hazard regression model with a change point. (Masters Thesis). Florida Atlantic University. Retrieved from http://purl.flvc.org/fau/fd/FA00004013

Chicago Manual of Style (16th Edition):

Abraha, Yonas Kidane. “Bayesian approach to an exponential hazard regression model with a change point.” 2014. Masters Thesis, Florida Atlantic University. Accessed August 10, 2020. http://purl.flvc.org/fau/fd/FA00004013.

MLA Handbook (7th Edition):

Abraha, Yonas Kidane. “Bayesian approach to an exponential hazard regression model with a change point.” 2014. Web. 10 Aug 2020.

Vancouver:

Abraha YK. Bayesian approach to an exponential hazard regression model with a change point. [Internet] [Masters thesis]. Florida Atlantic University; 2014. [cited 2020 Aug 10]. Available from: http://purl.flvc.org/fau/fd/FA00004013.

Council of Science Editors:

Abraha YK. Bayesian approach to an exponential hazard regression model with a change point. [Masters Thesis]. Florida Atlantic University; 2014. Available from: http://purl.flvc.org/fau/fd/FA00004013


Michigan State University

7. Chakraborty, Sayan. Estimation of statistical network and region-wise variable selection.

Degree: 2016, Michigan State University

Thesis Ph. D. Michigan State University. Statistics 2016

Network models are widely used to represent relations between actors or nodes. Recent studies of the network… (more)

Subjects/Keywords: Graph theory; System analysis; Bayesian statistical decision theory; Statistics

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APA (6th Edition):

Chakraborty, S. (2016). Estimation of statistical network and region-wise variable selection. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:4249

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):

Chakraborty, Sayan. “Estimation of statistical network and region-wise variable selection.” 2016. Thesis, Michigan State University. Accessed August 10, 2020. http://etd.lib.msu.edu/islandora/object/etd:4249.

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

MLA Handbook (7th Edition):

Chakraborty, Sayan. “Estimation of statistical network and region-wise variable selection.” 2016. Web. 10 Aug 2020.

Vancouver:

Chakraborty S. Estimation of statistical network and region-wise variable selection. [Internet] [Thesis]. Michigan State University; 2016. [cited 2020 Aug 10]. Available from: http://etd.lib.msu.edu/islandora/object/etd:4249.

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

Council of Science Editors:

Chakraborty S. Estimation of statistical network and region-wise variable selection. [Thesis]. Michigan State University; 2016. Available from: http://etd.lib.msu.edu/islandora/object/etd:4249

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

8. Rahman, Husneara. A comparison of Bayesian variable selection approaches for linear models.

Degree: Thesis (M.S.), 2014, Ball State University

Bayesian variable selection approaches are more powerful in discriminating among models regardless of whether these models under investigation are hierarchical or not. Although Bayesian approaches… (more)

Subjects/Keywords: Bayesian statistical decision theory.; Linear models (Statistics); Regression analysis.

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

APA (6th Edition):

Rahman, H. (2014). A comparison of Bayesian variable selection approaches for linear models. (Masters Thesis). Ball State University. Retrieved from http://cardinalscholar.bsu.edu/handle/123456789/198141

Chicago Manual of Style (16th Edition):

Rahman, Husneara. “A comparison of Bayesian variable selection approaches for linear models.” 2014. Masters Thesis, Ball State University. Accessed August 10, 2020. http://cardinalscholar.bsu.edu/handle/123456789/198141.

MLA Handbook (7th Edition):

Rahman, Husneara. “A comparison of Bayesian variable selection approaches for linear models.” 2014. Web. 10 Aug 2020.

Vancouver:

Rahman H. A comparison of Bayesian variable selection approaches for linear models. [Internet] [Masters thesis]. Ball State University; 2014. [cited 2020 Aug 10]. Available from: http://cardinalscholar.bsu.edu/handle/123456789/198141.

Council of Science Editors:

Rahman H. A comparison of Bayesian variable selection approaches for linear models. [Masters Thesis]. Ball State University; 2014. Available from: http://cardinalscholar.bsu.edu/handle/123456789/198141


University of Missouri – Columbia

9. Cheng, Chin-I. Bayesian smoothing spline analysis of variance models.

Degree: 2009, University of Missouri – Columbia

 Based on the pioneering work by Wahba (1990) in smoothing splines for nonparametric regression, Gu (2002) decomposed the regression function based on a tensor sum… (more)

Subjects/Keywords: Smoothing (Statistics); Nonparametric statistics; Regression analysis; Bayesian statistical decision theory; Gaussian processes

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APA (6th Edition):

Cheng, C. (2009). Bayesian smoothing spline analysis of variance models. (Thesis). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/10357

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):

Cheng, Chin-I. “Bayesian smoothing spline analysis of variance models.” 2009. Thesis, University of Missouri – Columbia. Accessed August 10, 2020. http://hdl.handle.net/10355/10357.

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

MLA Handbook (7th Edition):

Cheng, Chin-I. “Bayesian smoothing spline analysis of variance models.” 2009. Web. 10 Aug 2020.

Vancouver:

Cheng C. Bayesian smoothing spline analysis of variance models. [Internet] [Thesis]. University of Missouri – Columbia; 2009. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10355/10357.

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

Council of Science Editors:

Cheng C. Bayesian smoothing spline analysis of variance models. [Thesis]. University of Missouri – Columbia; 2009. Available from: http://hdl.handle.net/10355/10357

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


Columbia University

10. Teravainen, Timothy. Semiparametric Estimation of a Gaptime-Associated Hazard Function.

Degree: 2014, Columbia University

 This dissertation proposes a suite of novel Bayesian semiparametric estimators for a proportional hazard function associated with the gaptimes, or inter-arrival times, of a counting… (more)

Subjects/Keywords: Proportional hazards models; Survival analysis (Biometry); Bayesian statistical decision theory; Statistics; Electrical engineering

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APA (6th Edition):

Teravainen, T. (2014). Semiparametric Estimation of a Gaptime-Associated Hazard Function. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D80R9MDV

Chicago Manual of Style (16th Edition):

Teravainen, Timothy. “Semiparametric Estimation of a Gaptime-Associated Hazard Function.” 2014. Doctoral Dissertation, Columbia University. Accessed August 10, 2020. https://doi.org/10.7916/D80R9MDV.

MLA Handbook (7th Edition):

Teravainen, Timothy. “Semiparametric Estimation of a Gaptime-Associated Hazard Function.” 2014. Web. 10 Aug 2020.

Vancouver:

Teravainen T. Semiparametric Estimation of a Gaptime-Associated Hazard Function. [Internet] [Doctoral dissertation]. Columbia University; 2014. [cited 2020 Aug 10]. Available from: https://doi.org/10.7916/D80R9MDV.

Council of Science Editors:

Teravainen T. Semiparametric Estimation of a Gaptime-Associated Hazard Function. [Doctoral Dissertation]. Columbia University; 2014. Available from: https://doi.org/10.7916/D80R9MDV


UCLA

11. Yajima, Masanao. Bayesian Modeling of Interactions in Structured Heterogeneous Data.

Degree: Statistics, 2013, UCLA

 We propose Bayesian models tailored to infer complex patterns of dependence among heterogeneous sets of data. We consider highly structured information and illustrate modeling of… (more)

Subjects/Keywords: Statistics; Biostatistics; Bioinformatics; Bayesian Statistics; Decision Theory; Gaussian Graphical Models; Multiple Comparison; Multivariate Analysis; Structural Inference

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APA (6th Edition):

Yajima, M. (2013). Bayesian Modeling of Interactions in Structured Heterogeneous Data. (Thesis). UCLA. Retrieved from http://www.escholarship.org/uc/item/2gb4277x

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):

Yajima, Masanao. “Bayesian Modeling of Interactions in Structured Heterogeneous Data.” 2013. Thesis, UCLA. Accessed August 10, 2020. http://www.escholarship.org/uc/item/2gb4277x.

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

MLA Handbook (7th Edition):

Yajima, Masanao. “Bayesian Modeling of Interactions in Structured Heterogeneous Data.” 2013. Web. 10 Aug 2020.

Vancouver:

Yajima M. Bayesian Modeling of Interactions in Structured Heterogeneous Data. [Internet] [Thesis]. UCLA; 2013. [cited 2020 Aug 10]. Available from: http://www.escholarship.org/uc/item/2gb4277x.

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

Council of Science Editors:

Yajima M. Bayesian Modeling of Interactions in Structured Heterogeneous Data. [Thesis]. UCLA; 2013. Available from: http://www.escholarship.org/uc/item/2gb4277x

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


Rhodes University

12. Michell, Justin Walter. A review of generalized linear models for count data with emphasis on current geospatial procedures.

Degree: M.Com., Faculty of Science, Statistics, 2016, Rhodes University

 Analytical problems caused by over-fitting, confounding and non-independence in the data is a major challenge for variable selection. As more variables are tested against a… (more)

Subjects/Keywords: Spatial analysis (Statistics); Bayesian statistical decision theory; Geospatial data; Malaria  – Botswana  – Statistics; Malaria  – Botswana  – Research  – Statistical methods

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

APA (6th Edition):

Michell, J. W. (2016). A review of generalized linear models for count data with emphasis on current geospatial procedures. (Masters Thesis). Rhodes University. Retrieved from http://hdl.handle.net/10962/d1019989

Chicago Manual of Style (16th Edition):

Michell, Justin Walter. “A review of generalized linear models for count data with emphasis on current geospatial procedures.” 2016. Masters Thesis, Rhodes University. Accessed August 10, 2020. http://hdl.handle.net/10962/d1019989.

MLA Handbook (7th Edition):

Michell, Justin Walter. “A review of generalized linear models for count data with emphasis on current geospatial procedures.” 2016. Web. 10 Aug 2020.

Vancouver:

Michell JW. A review of generalized linear models for count data with emphasis on current geospatial procedures. [Internet] [Masters thesis]. Rhodes University; 2016. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10962/d1019989.

Council of Science Editors:

Michell JW. A review of generalized linear models for count data with emphasis on current geospatial procedures. [Masters Thesis]. Rhodes University; 2016. Available from: http://hdl.handle.net/10962/d1019989


Nelson Mandela Metropolitan University

13. Sarpong, Abeam Danso. Tolerance intervals for variance component models using a Bayesian simulation procedure.

Degree: Faculty of Science, 2013, Nelson Mandela Metropolitan University

 The estimation of variance components serves as an integral part of the evaluation of variation, and is of interest and required in a variety of… (more)

Subjects/Keywords: Bayesian statistical decision theory; Multilevel models (Statistics)

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APA (6th Edition):

Sarpong, A. D. (2013). Tolerance intervals for variance component models using a Bayesian simulation procedure. (Thesis). Nelson Mandela Metropolitan University. Retrieved from http://hdl.handle.net/10948/d1021025

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):

Sarpong, Abeam Danso. “Tolerance intervals for variance component models using a Bayesian simulation procedure.” 2013. Thesis, Nelson Mandela Metropolitan University. Accessed August 10, 2020. http://hdl.handle.net/10948/d1021025.

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

MLA Handbook (7th Edition):

Sarpong, Abeam Danso. “Tolerance intervals for variance component models using a Bayesian simulation procedure.” 2013. Web. 10 Aug 2020.

Vancouver:

Sarpong AD. Tolerance intervals for variance component models using a Bayesian simulation procedure. [Internet] [Thesis]. Nelson Mandela Metropolitan University; 2013. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10948/d1021025.

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

Council of Science Editors:

Sarpong AD. Tolerance intervals for variance component models using a Bayesian simulation procedure. [Thesis]. Nelson Mandela Metropolitan University; 2013. Available from: http://hdl.handle.net/10948/d1021025

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


Massey University

14. 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 (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 August 10, 2020. 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. 10 Aug 2020.

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 2020 Aug 10]. 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


Rutgers University

15. Thornton, Suzanne, 1991-. Advanced computing methods for statistical inference.

Degree: PhD, Statistics and Biostatistics, 2019, Rutgers University

 In this thesis, we provide some new and interesting solutions to problems of computational inference. In particular, the two problems we address are (1) How… (more)

Subjects/Keywords: Bayesian inference; Bayesian statistical decision theory; Mathematical statistics

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APA (6th Edition):

Thornton, Suzanne, 1. (2019). Advanced computing methods for statistical inference. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/61966/

Chicago Manual of Style (16th Edition):

Thornton, Suzanne, 1991-. “Advanced computing methods for statistical inference.” 2019. Doctoral Dissertation, Rutgers University. Accessed August 10, 2020. https://rucore.libraries.rutgers.edu/rutgers-lib/61966/.

MLA Handbook (7th Edition):

Thornton, Suzanne, 1991-. “Advanced computing methods for statistical inference.” 2019. Web. 10 Aug 2020.

Vancouver:

Thornton, Suzanne 1. Advanced computing methods for statistical inference. [Internet] [Doctoral dissertation]. Rutgers University; 2019. [cited 2020 Aug 10]. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61966/.

Council of Science Editors:

Thornton, Suzanne 1. Advanced computing methods for statistical inference. [Doctoral Dissertation]. Rutgers University; 2019. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/61966/


The Ohio State University

16. Toman, Blaza. Bayesian optimal experimental design for the comparison of treatment with a control in the analysis of variance setting .

Degree: PhD, Graduate School, 1987, The Ohio State University

Subjects/Keywords: Statistics; Analysis of variance; Bayesian statistical decision theory

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APA (6th Edition):

Toman, B. (1987). Bayesian optimal experimental design for the comparison of treatment with a control in the analysis of variance setting . (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1487330761216343

Chicago Manual of Style (16th Edition):

Toman, Blaza. “Bayesian optimal experimental design for the comparison of treatment with a control in the analysis of variance setting .” 1987. Doctoral Dissertation, The Ohio State University. Accessed August 10, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487330761216343.

MLA Handbook (7th Edition):

Toman, Blaza. “Bayesian optimal experimental design for the comparison of treatment with a control in the analysis of variance setting .” 1987. Web. 10 Aug 2020.

Vancouver:

Toman B. Bayesian optimal experimental design for the comparison of treatment with a control in the analysis of variance setting . [Internet] [Doctoral dissertation]. The Ohio State University; 1987. [cited 2020 Aug 10]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1487330761216343.

Council of Science Editors:

Toman B. Bayesian optimal experimental design for the comparison of treatment with a control in the analysis of variance setting . [Doctoral Dissertation]. The Ohio State University; 1987. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1487330761216343


The Ohio State University

17. Wright, Tommy. Bayes allocation and sequential estimation in stratified populations.

Degree: PhD, Graduate School, 1977, The Ohio State University

Subjects/Keywords: Statistics; Sequential analysis; Bayesian statistical decision theory

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APA (6th Edition):

Wright, T. (1977). Bayes allocation and sequential estimation in stratified populations. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1487069564240417

Chicago Manual of Style (16th Edition):

Wright, Tommy. “Bayes allocation and sequential estimation in stratified populations.” 1977. Doctoral Dissertation, The Ohio State University. Accessed August 10, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487069564240417.

MLA Handbook (7th Edition):

Wright, Tommy. “Bayes allocation and sequential estimation in stratified populations.” 1977. Web. 10 Aug 2020.

Vancouver:

Wright T. Bayes allocation and sequential estimation in stratified populations. [Internet] [Doctoral dissertation]. The Ohio State University; 1977. [cited 2020 Aug 10]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1487069564240417.

Council of Science Editors:

Wright T. Bayes allocation and sequential estimation in stratified populations. [Doctoral Dissertation]. The Ohio State University; 1977. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1487069564240417


Baylor University

18. McBride, John Jacob. Conjugate hierarchical models for spatial data: an application on an optimal selection procedure.

Degree: PhD, Statistical Sciences., 2006, Baylor University

 The theory of generalized linear models provides a unifying class of statistical distributions that can be used to model both discrete and continuous events. In… (more)

Subjects/Keywords: Spatial analysis (Statistics).; Bayesian statistical decision theory.

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APA (6th Edition):

McBride, J. J. (2006). Conjugate hierarchical models for spatial data: an application on an optimal selection procedure. (Doctoral Dissertation). Baylor University. Retrieved from http://hdl.handle.net/2104/3955

Chicago Manual of Style (16th Edition):

McBride, John Jacob. “Conjugate hierarchical models for spatial data: an application on an optimal selection procedure.” 2006. Doctoral Dissertation, Baylor University. Accessed August 10, 2020. http://hdl.handle.net/2104/3955.

MLA Handbook (7th Edition):

McBride, John Jacob. “Conjugate hierarchical models for spatial data: an application on an optimal selection procedure.” 2006. Web. 10 Aug 2020.

Vancouver:

McBride JJ. Conjugate hierarchical models for spatial data: an application on an optimal selection procedure. [Internet] [Doctoral dissertation]. Baylor University; 2006. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/2104/3955.

Council of Science Editors:

McBride JJ. Conjugate hierarchical models for spatial data: an application on an optimal selection procedure. [Doctoral Dissertation]. Baylor University; 2006. Available from: http://hdl.handle.net/2104/3955


University of Central Florida

19. Rinke, Caitlin. Selective Multivariate Applications In Forensic Science.

Degree: 2012, University of Central Florida

 A 2009 report published by the National Research Council addressed the need for improvements in the field of forensic science. In the report emphasis was… (more)

Subjects/Keywords: Multivariate statistics; forensic sciences; spectroscopy; nonparametric statistics; principal component analysis; target factor analysis; bayesian decision theory; Chemistry; Dissertations, Academic  – Sciences, Sciences  – Dissertations, Academic

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

APA (6th Edition):

Rinke, C. (2012). Selective Multivariate Applications In Forensic Science. (Doctoral Dissertation). University of Central Florida. Retrieved from https://stars.library.ucf.edu/etd/2296

Chicago Manual of Style (16th Edition):

Rinke, Caitlin. “Selective Multivariate Applications In Forensic Science.” 2012. Doctoral Dissertation, University of Central Florida. Accessed August 10, 2020. https://stars.library.ucf.edu/etd/2296.

MLA Handbook (7th Edition):

Rinke, Caitlin. “Selective Multivariate Applications In Forensic Science.” 2012. Web. 10 Aug 2020.

Vancouver:

Rinke C. Selective Multivariate Applications In Forensic Science. [Internet] [Doctoral dissertation]. University of Central Florida; 2012. [cited 2020 Aug 10]. Available from: https://stars.library.ucf.edu/etd/2296.

Council of Science Editors:

Rinke C. Selective Multivariate Applications In Forensic Science. [Doctoral Dissertation]. University of Central Florida; 2012. Available from: https://stars.library.ucf.edu/etd/2296


Columbia University

20. Sahai, Swupnil. Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology.

Degree: 2018, Columbia University

 This thesis includes three parts. The overarching theme is how to analyze structured hierarchical data, with applications to astronomy and sociology. The first part discusses… (more)

Subjects/Keywords: Statistics; Astronomy; Sociology; Bayesian statistical decision theory; Multilevel models (Statistics)

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

APA (6th Edition):

Sahai, S. (2018). Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D83R15HQ

Chicago Manual of Style (16th Edition):

Sahai, Swupnil. “Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology.” 2018. Doctoral Dissertation, Columbia University. Accessed August 10, 2020. https://doi.org/10.7916/D83R15HQ.

MLA Handbook (7th Edition):

Sahai, Swupnil. “Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology.” 2018. Web. 10 Aug 2020.

Vancouver:

Sahai S. Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology. [Internet] [Doctoral dissertation]. Columbia University; 2018. [cited 2020 Aug 10]. Available from: https://doi.org/10.7916/D83R15HQ.

Council of Science Editors:

Sahai S. Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology. [Doctoral Dissertation]. Columbia University; 2018. Available from: https://doi.org/10.7916/D83R15HQ


University of Missouri – Columbia

21. Gao, Xiaoming, 1964-. Bayesian spatial models for adjusting nonresponse in small area estimation.

Degree: 2010, University of Missouri – Columbia

 [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] There are two kinds of nonresponse: item nonresponse and unit nonresponse. Inferences made from respondents… (more)

Subjects/Keywords: Bayesian statistical decision theory; Response surfaces (Statistics); Nonresponse (Statistics)

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APA (6th Edition):

Gao, Xiaoming, 1. (2010). Bayesian spatial models for adjusting nonresponse in small area estimation. (Thesis). University of Missouri – Columbia. Retrieved from https://doi.org/10.32469/10355/9021

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):

Gao, Xiaoming, 1964-. “Bayesian spatial models for adjusting nonresponse in small area estimation.” 2010. Thesis, University of Missouri – Columbia. Accessed August 10, 2020. https://doi.org/10.32469/10355/9021.

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

MLA Handbook (7th Edition):

Gao, Xiaoming, 1964-. “Bayesian spatial models for adjusting nonresponse in small area estimation.” 2010. Web. 10 Aug 2020.

Vancouver:

Gao, Xiaoming 1. Bayesian spatial models for adjusting nonresponse in small area estimation. [Internet] [Thesis]. University of Missouri – Columbia; 2010. [cited 2020 Aug 10]. Available from: https://doi.org/10.32469/10355/9021.

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

Council of Science Editors:

Gao, Xiaoming 1. Bayesian spatial models for adjusting nonresponse in small area estimation. [Thesis]. University of Missouri – Columbia; 2010. Available from: https://doi.org/10.32469/10355/9021

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


University of Missouri – Columbia

22. Cheng, Chin-I. Bayesian smoothing spline analysis of variance models.

Degree: 2009, University of Missouri – Columbia

 Based on the pioneering work by Wahba (1990) in smoothing splines for nonparametric regression, Gu (2002) decomposed the regression function based on a tensor sum… (more)

Subjects/Keywords: Smoothing (Statistics); Nonparametric statistics; Regression analysis; Bayesian statistical decision theory; Gaussian processes

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

APA (6th Edition):

Cheng, C. (2009). Bayesian smoothing spline analysis of variance models. (Thesis). University of Missouri – Columbia. Retrieved from https://doi.org/10.32469/10355/10357

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):

Cheng, Chin-I. “Bayesian smoothing spline analysis of variance models.” 2009. Thesis, University of Missouri – Columbia. Accessed August 10, 2020. https://doi.org/10.32469/10355/10357.

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

MLA Handbook (7th Edition):

Cheng, Chin-I. “Bayesian smoothing spline analysis of variance models.” 2009. Web. 10 Aug 2020.

Vancouver:

Cheng C. Bayesian smoothing spline analysis of variance models. [Internet] [Thesis]. University of Missouri – Columbia; 2009. [cited 2020 Aug 10]. Available from: https://doi.org/10.32469/10355/10357.

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

Council of Science Editors:

Cheng C. Bayesian smoothing spline analysis of variance models. [Thesis]. University of Missouri – Columbia; 2009. Available from: https://doi.org/10.32469/10355/10357

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


University of Missouri – Columbia

23. Sun, Xiaoqian, 1967-. Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project.

Degree: PhD, 2006, University of Missouri – Columbia

 The first part studies the problem of estimating the covariance matrix in a star-shaped model with missing data. By introducing a class of priors based… (more)

Subjects/Keywords: Spatial analysis (Statistics); Bayesian statistical decision theory; Analysis of covariance; Forest restoration

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APA (6th Edition):

Sun, Xiaoqian, 1. (2006). Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project. (Doctoral Dissertation). University of Missouri – Columbia. Retrieved from https://doi.org/10.32469/10355/4477

Chicago Manual of Style (16th Edition):

Sun, Xiaoqian, 1967-. “Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project.” 2006. Doctoral Dissertation, University of Missouri – Columbia. Accessed August 10, 2020. https://doi.org/10.32469/10355/4477.

MLA Handbook (7th Edition):

Sun, Xiaoqian, 1967-. “Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project.” 2006. Web. 10 Aug 2020.

Vancouver:

Sun, Xiaoqian 1. Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project. [Internet] [Doctoral dissertation]. University of Missouri – Columbia; 2006. [cited 2020 Aug 10]. Available from: https://doi.org/10.32469/10355/4477.

Council of Science Editors:

Sun, Xiaoqian 1. Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project. [Doctoral Dissertation]. University of Missouri – Columbia; 2006. Available from: https://doi.org/10.32469/10355/4477


Texas State University – San Marcos

24. Kringen, Jonathan Allen. Validating a Bayesian Model for Linking Serial Crimes Through Simulation.

Degree: PhD, Criminal Justice, 2014, Texas State University – San Marcos

 Crime linkage analysis tries to determine which crimes were committed by the same offender. This is an important police investigative function, as research has shown… (more)

Subjects/Keywords: Crime linkage; Serial crime; Crime analysis; Criminal behavior; Criminal methods; Crime analysis; Criminal behavior, Prediction of; Bayesian statistical decision theory; Mathematical statistics

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APA (6th Edition):

Kringen, J. A. (2014). Validating a Bayesian Model for Linking Serial Crimes Through Simulation. (Doctoral Dissertation). Texas State University – San Marcos. Retrieved from https://digital.library.txstate.edu/handle/10877/4954

Chicago Manual of Style (16th Edition):

Kringen, Jonathan Allen. “Validating a Bayesian Model for Linking Serial Crimes Through Simulation.” 2014. Doctoral Dissertation, Texas State University – San Marcos. Accessed August 10, 2020. https://digital.library.txstate.edu/handle/10877/4954.

MLA Handbook (7th Edition):

Kringen, Jonathan Allen. “Validating a Bayesian Model for Linking Serial Crimes Through Simulation.” 2014. Web. 10 Aug 2020.

Vancouver:

Kringen JA. Validating a Bayesian Model for Linking Serial Crimes Through Simulation. [Internet] [Doctoral dissertation]. Texas State University – San Marcos; 2014. [cited 2020 Aug 10]. Available from: https://digital.library.txstate.edu/handle/10877/4954.

Council of Science Editors:

Kringen JA. Validating a Bayesian Model for Linking Serial Crimes Through Simulation. [Doctoral Dissertation]. Texas State University – San Marcos; 2014. Available from: https://digital.library.txstate.edu/handle/10877/4954


University of Missouri – Columbia

25. Sun, Xiaoqian, 1967-. Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project.

Degree: PhD, 2006, University of Missouri – Columbia

 The first part studies the problem of estimating the covariance matrix in a star-shaped model with missing data. By introducing a class of priors based… (more)

Subjects/Keywords: Spatial analysis (Statistics); Bayesian statistical decision theory; Analysis of covariance; Forest restoration

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

APA (6th Edition):

Sun, Xiaoqian, 1. (2006). Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project. (Doctoral Dissertation). University of Missouri – Columbia. Retrieved from http://hdl.handle.net/10355/4477

Chicago Manual of Style (16th Edition):

Sun, Xiaoqian, 1967-. “Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project.” 2006. Doctoral Dissertation, University of Missouri – Columbia. Accessed August 10, 2020. http://hdl.handle.net/10355/4477.

MLA Handbook (7th Edition):

Sun, Xiaoqian, 1967-. “Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project.” 2006. Web. 10 Aug 2020.

Vancouver:

Sun, Xiaoqian 1. Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project. [Internet] [Doctoral dissertation]. University of Missouri – Columbia; 2006. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10355/4477.

Council of Science Editors:

Sun, Xiaoqian 1. Bayesian spatial data analysis with application to the Missouri Ozark forest ecosystem project. [Doctoral Dissertation]. University of Missouri – Columbia; 2006. Available from: http://hdl.handle.net/10355/4477


Columbia University

26. Cheng, Edward K. Selected Legal Applications for Bayesian Methods.

Degree: 2018, Columbia University

 This dissertation offers three contexts in which Bayesian methods can address tricky problems in the legal system. Chapter 1 offers a method for attacking case… (more)

Subjects/Keywords: Statistics; Law; Bayesian statistical decision theory; Law – Statistical methods

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APA (6th Edition):

Cheng, E. K. (2018). Selected Legal Applications for Bayesian Methods. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8H71Z8N

Chicago Manual of Style (16th Edition):

Cheng, Edward K. “Selected Legal Applications for Bayesian Methods.” 2018. Doctoral Dissertation, Columbia University. Accessed August 10, 2020. https://doi.org/10.7916/D8H71Z8N.

MLA Handbook (7th Edition):

Cheng, Edward K. “Selected Legal Applications for Bayesian Methods.” 2018. Web. 10 Aug 2020.

Vancouver:

Cheng EK. Selected Legal Applications for Bayesian Methods. [Internet] [Doctoral dissertation]. Columbia University; 2018. [cited 2020 Aug 10]. Available from: https://doi.org/10.7916/D8H71Z8N.

Council of Science Editors:

Cheng EK. Selected Legal Applications for Bayesian Methods. [Doctoral Dissertation]. Columbia University; 2018. Available from: https://doi.org/10.7916/D8H71Z8N


Columbia University

27. Chen, Jingjing. A Bayesian Approach to the Understanding of Exoplanet Populations and the Origin of Life.

Degree: 2018, Columbia University

 The study of extrasolar planets, or exoplanets for short, has developed rapidly over the last decade. While we have spent much effort building both ground-based… (more)

Subjects/Keywords: Astronomy; Extrasolar planets; Life – Origin; Statistics; Bayesian statistical decision theory

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APA (6th Edition):

Chen, J. (2018). A Bayesian Approach to the Understanding of Exoplanet Populations and the Origin of Life. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8QN7QPD

Chicago Manual of Style (16th Edition):

Chen, Jingjing. “A Bayesian Approach to the Understanding of Exoplanet Populations and the Origin of Life.” 2018. Doctoral Dissertation, Columbia University. Accessed August 10, 2020. https://doi.org/10.7916/D8QN7QPD.

MLA Handbook (7th Edition):

Chen, Jingjing. “A Bayesian Approach to the Understanding of Exoplanet Populations and the Origin of Life.” 2018. Web. 10 Aug 2020.

Vancouver:

Chen J. A Bayesian Approach to the Understanding of Exoplanet Populations and the Origin of Life. [Internet] [Doctoral dissertation]. Columbia University; 2018. [cited 2020 Aug 10]. Available from: https://doi.org/10.7916/D8QN7QPD.

Council of Science Editors:

Chen J. A Bayesian Approach to the Understanding of Exoplanet Populations and the Origin of Life. [Doctoral Dissertation]. Columbia University; 2018. Available from: https://doi.org/10.7916/D8QN7QPD


Rutgers University

28. Cheng, Jerry Q., 1965-. Bayesian methods for non-standard missing data problems.

Degree: PhD, Statistics and Biostatistics, 2010, Rutgers University

Missing data presents challenges to statistical analysis in many applications such as clinical trials, cluster detection, etc. This thesis analyzes and develops methodologies in some… (more)

Subjects/Keywords: Bayesian statistical decision theory; Missing observations (Statistics) – Mathematical models

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APA (6th Edition):

Cheng, Jerry Q., 1. (2010). Bayesian methods for non-standard missing data problems. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052996

Chicago Manual of Style (16th Edition):

Cheng, Jerry Q., 1965-. “Bayesian methods for non-standard missing data problems.” 2010. Doctoral Dissertation, Rutgers University. Accessed August 10, 2020. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052996.

MLA Handbook (7th Edition):

Cheng, Jerry Q., 1965-. “Bayesian methods for non-standard missing data problems.” 2010. Web. 10 Aug 2020.

Vancouver:

Cheng, Jerry Q. 1. Bayesian methods for non-standard missing data problems. [Internet] [Doctoral dissertation]. Rutgers University; 2010. [cited 2020 Aug 10]. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052996.

Council of Science Editors:

Cheng, Jerry Q. 1. Bayesian methods for non-standard missing data problems. [Doctoral Dissertation]. Rutgers University; 2010. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052996


Colorado State University

29. Brogan, John. Development of a decision threshold for radiological source detection utilizing Bayesian statistical techniques applied to gross count measurements.

Degree: PhD, Environmental and Radiological Health Sciences, 2018, Colorado State University

 Numerous studies have been published using Bayesian statistics in source localization and identification, characterization of radioactive samples, and uncertainty analysis; but there is a limited… (more)

Subjects/Keywords: decision threshold; gross counts; statistical modeling; detection; Bayesian statistics; radiation

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APA (6th Edition):

Brogan, J. (2018). Development of a decision threshold for radiological source detection utilizing Bayesian statistical techniques applied to gross count measurements. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/191481

Chicago Manual of Style (16th Edition):

Brogan, John. “Development of a decision threshold for radiological source detection utilizing Bayesian statistical techniques applied to gross count measurements.” 2018. Doctoral Dissertation, Colorado State University. Accessed August 10, 2020. http://hdl.handle.net/10217/191481.

MLA Handbook (7th Edition):

Brogan, John. “Development of a decision threshold for radiological source detection utilizing Bayesian statistical techniques applied to gross count measurements.” 2018. Web. 10 Aug 2020.

Vancouver:

Brogan J. Development of a decision threshold for radiological source detection utilizing Bayesian statistical techniques applied to gross count measurements. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2020 Aug 10]. Available from: http://hdl.handle.net/10217/191481.

Council of Science Editors:

Brogan J. Development of a decision threshold for radiological source detection utilizing Bayesian statistical techniques applied to gross count measurements. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/191481


Michigan State University

30. Matney, Jason Andrew. Bayesian hierarchical models for environmental datasets.

Degree: 2014, Michigan State University

Thesis M.S. Michigan State University. Geography - Master of Science 2014.

This thesis explores the applicability of Bayesian spatial models for predicting the occurrence of… (more)

Subjects/Keywords: Permafrost – Alaska – Forecasting; Geography – Statistical methods; Multilevel models (Statistics); Bayesian statistical decision theory; Geography; Statistics

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APA (6th Edition):

Matney, J. A. (2014). Bayesian hierarchical models for environmental datasets. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:2690

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):

Matney, Jason Andrew. “Bayesian hierarchical models for environmental datasets.” 2014. Thesis, Michigan State University. Accessed August 10, 2020. http://etd.lib.msu.edu/islandora/object/etd:2690.

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

MLA Handbook (7th Edition):

Matney, Jason Andrew. “Bayesian hierarchical models for environmental datasets.” 2014. Web. 10 Aug 2020.

Vancouver:

Matney JA. Bayesian hierarchical models for environmental datasets. [Internet] [Thesis]. Michigan State University; 2014. [cited 2020 Aug 10]. Available from: http://etd.lib.msu.edu/islandora/object/etd:2690.

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

Council of Science Editors:

Matney JA. Bayesian hierarchical models for environmental datasets. [Thesis]. Michigan State University; 2014. Available from: http://etd.lib.msu.edu/islandora/object/etd:2690

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

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