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You searched for subject:(Bayesian hierarchical model). Showing records 1 – 30 of 106 total matches.

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Universitat de Valencia

1. Rodríguez de Rivera Ortega, Oscar. Spatio temporal modeling of species distribution .

Degree: 2019, Universitat de Valencia

 The aim of this thesis is study spatial distribution of different groups from different perspectives and to analyse the different approaches to this problem. We… (more)

Subjects/Keywords: ecology; species distribution model; bayesian hierarchical model

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APA (6th Edition):

Rodríguez de Rivera Ortega, O. (2019). Spatio temporal modeling of species distribution . (Doctoral Dissertation). Universitat de Valencia. Retrieved from http://hdl.handle.net/10550/68427

Chicago Manual of Style (16th Edition):

Rodríguez de Rivera Ortega, Oscar. “Spatio temporal modeling of species distribution .” 2019. Doctoral Dissertation, Universitat de Valencia. Accessed October 15, 2019. http://hdl.handle.net/10550/68427.

MLA Handbook (7th Edition):

Rodríguez de Rivera Ortega, Oscar. “Spatio temporal modeling of species distribution .” 2019. Web. 15 Oct 2019.

Vancouver:

Rodríguez de Rivera Ortega O. Spatio temporal modeling of species distribution . [Internet] [Doctoral dissertation]. Universitat de Valencia; 2019. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/10550/68427.

Council of Science Editors:

Rodríguez de Rivera Ortega O. Spatio temporal modeling of species distribution . [Doctoral Dissertation]. Universitat de Valencia; 2019. Available from: http://hdl.handle.net/10550/68427


University of Southern California

2. Wang, Li. Modeling and analysis of nanostructure growth process kinetics and variations for scalable nanomanufacturing.

Degree: PhD, Industrial and Systems Engineering, 2013, University of Southern California

 Nanomanufacturing is currently a major bottleneck that hinders the transformation of nanotechnology from laboratory to industrial applications. Due to both limited process understanding and control,… (more)

Subjects/Keywords: statistical modeling; nano; Bayesian hierarchical model

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APA (6th Edition):

Wang, L. (2013). Modeling and analysis of nanostructure growth process kinetics and variations for scalable nanomanufacturing. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/347602/rec/4115

Chicago Manual of Style (16th Edition):

Wang, Li. “Modeling and analysis of nanostructure growth process kinetics and variations for scalable nanomanufacturing.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 15, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/347602/rec/4115.

MLA Handbook (7th Edition):

Wang, Li. “Modeling and analysis of nanostructure growth process kinetics and variations for scalable nanomanufacturing.” 2013. Web. 15 Oct 2019.

Vancouver:

Wang L. Modeling and analysis of nanostructure growth process kinetics and variations for scalable nanomanufacturing. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Oct 15]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/347602/rec/4115.

Council of Science Editors:

Wang L. Modeling and analysis of nanostructure growth process kinetics and variations for scalable nanomanufacturing. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/347602/rec/4115


University of Southern California

3. Liang, Wei. Bayesian hierarchical models in genetic association studies.

Degree: PhD, Biostatistics, 2013, University of Southern California

 Genetic association studies aim to find the genetic variations that are associated with phenotypes (traits). In the last decade, genome-wide association studies have been proposed… (more)

Subjects/Keywords: Bayesian; hierarchical model; genetic association study

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APA (6th Edition):

Liang, W. (2013). Bayesian hierarchical models in genetic association studies. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/344907/rec/1041

Chicago Manual of Style (16th Edition):

Liang, Wei. “Bayesian hierarchical models in genetic association studies.” 2013. Doctoral Dissertation, University of Southern California. Accessed October 15, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/344907/rec/1041.

MLA Handbook (7th Edition):

Liang, Wei. “Bayesian hierarchical models in genetic association studies.” 2013. Web. 15 Oct 2019.

Vancouver:

Liang W. Bayesian hierarchical models in genetic association studies. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Oct 15]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/344907/rec/1041.

Council of Science Editors:

Liang W. Bayesian hierarchical models in genetic association studies. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/344907/rec/1041


The Ohio State University

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

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

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

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

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

White, Staci A. “Quantifying Model Error in Bayesian Parameter Estimation.” 2015. Doctoral Dissertation, The Ohio State University. Accessed October 15, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1433771825.

MLA Handbook (7th Edition):

White, Staci A. “Quantifying Model Error in Bayesian Parameter Estimation.” 2015. Web. 15 Oct 2019.

Vancouver:

White SA. Quantifying Model Error in Bayesian Parameter Estimation. [Internet] [Doctoral dissertation]. The Ohio State University; 2015. [cited 2019 Oct 15]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1433771825.

Council of Science Editors:

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


Texas A&M University

5. Xia, Haifeng. Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.

Degree: 2010, Texas A&M University

 This dissertation presents a Bayesian hierarchical model to combine two-resolution metrology data for inspecting the geometric quality of manufactured parts. The high- resolution data points… (more)

Subjects/Keywords: Bayesian hierarchical model; Bayesian model averaging; Data combining; Gaussian process; Misalignment; Two-resolution data

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APA (6th Edition):

Xia, H. (2010). Bayesian Hierarchical Model for Combining Two-resolution Metrology Data. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164

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):

Xia, Haifeng. “Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.” 2010. Thesis, Texas A&M University. Accessed October 15, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164.

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

MLA Handbook (7th Edition):

Xia, Haifeng. “Bayesian Hierarchical Model for Combining Two-resolution Metrology Data.” 2010. Web. 15 Oct 2019.

Vancouver:

Xia H. Bayesian Hierarchical Model for Combining Two-resolution Metrology Data. [Internet] [Thesis]. Texas A&M University; 2010. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164.

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

Council of Science Editors:

Xia H. Bayesian Hierarchical Model for Combining Two-resolution Metrology Data. [Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2008-12-164

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


Rice University

6. Wadsworth, W Duncan. Bayesian Methods for the Analysis of Microbiome Data.

Degree: PhD, Engineering, 2016, Rice University

 Bacteria, archaea, viruses, and fungi are present in large numbers both on and inside of our bodies. On average, only one in ten of “our”… (more)

Subjects/Keywords: Bayesian hierarchical model; Data integration; Dirichlet-Multinomial; Microbiome data; Variable selection; Multiple testing; Bayesian nonparametrics

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APA (6th Edition):

Wadsworth, W. D. (2016). Bayesian Methods for the Analysis of Microbiome Data. (Doctoral Dissertation). Rice University. Retrieved from http://hdl.handle.net/1911/95977

Chicago Manual of Style (16th Edition):

Wadsworth, W Duncan. “Bayesian Methods for the Analysis of Microbiome Data.” 2016. Doctoral Dissertation, Rice University. Accessed October 15, 2019. http://hdl.handle.net/1911/95977.

MLA Handbook (7th Edition):

Wadsworth, W Duncan. “Bayesian Methods for the Analysis of Microbiome Data.” 2016. Web. 15 Oct 2019.

Vancouver:

Wadsworth WD. Bayesian Methods for the Analysis of Microbiome Data. [Internet] [Doctoral dissertation]. Rice University; 2016. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1911/95977.

Council of Science Editors:

Wadsworth WD. Bayesian Methods for the Analysis of Microbiome Data. [Doctoral Dissertation]. Rice University; 2016. Available from: http://hdl.handle.net/1911/95977


University of Ghana

7. Anno-Kwakye, R. Bayesian Hierarchical Model With Classification And Regression Tree In Predicting Loan Default .

Degree: 2017, University of Ghana

Bayesian modelling as well as decision tree methods are some of the efficacious classification methods in credit scoring applications. Application of these methods to credit… (more)

Subjects/Keywords: Bayesian Hierarchical Model; Classification; Regression Tree; Loan Default

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APA (6th Edition):

Anno-Kwakye, R. (2017). Bayesian Hierarchical Model With Classification And Regression Tree In Predicting Loan Default . (Masters Thesis). University of Ghana. Retrieved from http://ugspace.ug.edu.gh/handle/123456789/23191

Chicago Manual of Style (16th Edition):

Anno-Kwakye, R. “Bayesian Hierarchical Model With Classification And Regression Tree In Predicting Loan Default .” 2017. Masters Thesis, University of Ghana. Accessed October 15, 2019. http://ugspace.ug.edu.gh/handle/123456789/23191.

MLA Handbook (7th Edition):

Anno-Kwakye, R. “Bayesian Hierarchical Model With Classification And Regression Tree In Predicting Loan Default .” 2017. Web. 15 Oct 2019.

Vancouver:

Anno-Kwakye R. Bayesian Hierarchical Model With Classification And Regression Tree In Predicting Loan Default . [Internet] [Masters thesis]. University of Ghana; 2017. [cited 2019 Oct 15]. Available from: http://ugspace.ug.edu.gh/handle/123456789/23191.

Council of Science Editors:

Anno-Kwakye R. Bayesian Hierarchical Model With Classification And Regression Tree In Predicting Loan Default . [Masters Thesis]. University of Ghana; 2017. Available from: http://ugspace.ug.edu.gh/handle/123456789/23191


University of Washington

8. Azose, Jonathan Jerome. Projection and Estimation of International Migration.

Degree: PhD, 2017, University of Washington

 I propose techniques for improving both estimation and projection of international migration. By applying a Bayesian hierarchical modeling approach to net migration data, I produce… (more)

Subjects/Keywords: Bayesian Hierarchical Model; Correlation; Estimation; International Migration; Projection; Statistics; Demography; statistics

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APA (6th Edition):

Azose, J. J. (2017). Projection and Estimation of International Migration. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/38221

Chicago Manual of Style (16th Edition):

Azose, Jonathan Jerome. “Projection and Estimation of International Migration.” 2017. Doctoral Dissertation, University of Washington. Accessed October 15, 2019. http://hdl.handle.net/1773/38221.

MLA Handbook (7th Edition):

Azose, Jonathan Jerome. “Projection and Estimation of International Migration.” 2017. Web. 15 Oct 2019.

Vancouver:

Azose JJ. Projection and Estimation of International Migration. [Internet] [Doctoral dissertation]. University of Washington; 2017. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1773/38221.

Council of Science Editors:

Azose JJ. Projection and Estimation of International Migration. [Doctoral Dissertation]. University of Washington; 2017. Available from: http://hdl.handle.net/1773/38221


University of Washington

9. Coley, Rebecca Yates. Bayesian Hierarchical Frailty Models for Heterogeneity in Risk.

Degree: PhD, 2014, University of Washington

 The effect of an intervention or exposure on time-to-event is most commonly estimated with the Cox model, which assumes proportional hazards. When heterogeneity in risk… (more)

Subjects/Keywords: Bayesian analysis; Frailty; Heterogeneity; Hierarchical model; HIV prevention; Survival analysis; Biostatistics

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APA (6th Edition):

Coley, R. Y. (2014). Bayesian Hierarchical Frailty Models for Heterogeneity in Risk. (Doctoral Dissertation). University of Washington. Retrieved from http://hdl.handle.net/1773/26396

Chicago Manual of Style (16th Edition):

Coley, Rebecca Yates. “Bayesian Hierarchical Frailty Models for Heterogeneity in Risk.” 2014. Doctoral Dissertation, University of Washington. Accessed October 15, 2019. http://hdl.handle.net/1773/26396.

MLA Handbook (7th Edition):

Coley, Rebecca Yates. “Bayesian Hierarchical Frailty Models for Heterogeneity in Risk.” 2014. Web. 15 Oct 2019.

Vancouver:

Coley RY. Bayesian Hierarchical Frailty Models for Heterogeneity in Risk. [Internet] [Doctoral dissertation]. University of Washington; 2014. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1773/26396.

Council of Science Editors:

Coley RY. Bayesian Hierarchical Frailty Models for Heterogeneity in Risk. [Doctoral Dissertation]. University of Washington; 2014. Available from: http://hdl.handle.net/1773/26396


Brunel University

10. Tan, Hwei-Yang. Statistical methods for the analysis of corrosion data for integrity assessments.

Degree: PhD, 2017, Brunel University

 In the oil and gas industry, statistical methods have been used for corrosion analysis for various asset systems such as pipelines, storage tanks, and so… (more)

Subjects/Keywords: Remaining useful life; Bayesian hierarchical model; Piping deadleg; Conductor pipe

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APA (6th Edition):

Tan, H. (2017). Statistical methods for the analysis of corrosion data for integrity assessments. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/15275 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764816

Chicago Manual of Style (16th Edition):

Tan, Hwei-Yang. “Statistical methods for the analysis of corrosion data for integrity assessments.” 2017. Doctoral Dissertation, Brunel University. Accessed October 15, 2019. http://bura.brunel.ac.uk/handle/2438/15275 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764816.

MLA Handbook (7th Edition):

Tan, Hwei-Yang. “Statistical methods for the analysis of corrosion data for integrity assessments.” 2017. Web. 15 Oct 2019.

Vancouver:

Tan H. Statistical methods for the analysis of corrosion data for integrity assessments. [Internet] [Doctoral dissertation]. Brunel University; 2017. [cited 2019 Oct 15]. Available from: http://bura.brunel.ac.uk/handle/2438/15275 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764816.

Council of Science Editors:

Tan H. Statistical methods for the analysis of corrosion data for integrity assessments. [Doctoral Dissertation]. Brunel University; 2017. Available from: http://bura.brunel.ac.uk/handle/2438/15275 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764816


Boston University

11. McIntosh, Avery Isaac. Extensions to Bayesian generalized linear mixed effects models for household tuberculosis transmission.

Degree: PhD, Biostatistics, 2017, Boston University

 Understanding tuberculosis transmission is vital for efforts at interrupting the spread of disease. Household contact studies that follow persons sharing a household with a TB… (more)

Subjects/Keywords: Biostatistics; Bayesian mixed effects; Generalized linear model; Hierarchical models; Infection; Tuberculosis

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APA (6th Edition):

McIntosh, A. I. (2017). Extensions to Bayesian generalized linear mixed effects models for household tuberculosis transmission. (Doctoral Dissertation). Boston University. Retrieved from http://hdl.handle.net/2144/22451

Chicago Manual of Style (16th Edition):

McIntosh, Avery Isaac. “Extensions to Bayesian generalized linear mixed effects models for household tuberculosis transmission.” 2017. Doctoral Dissertation, Boston University. Accessed October 15, 2019. http://hdl.handle.net/2144/22451.

MLA Handbook (7th Edition):

McIntosh, Avery Isaac. “Extensions to Bayesian generalized linear mixed effects models for household tuberculosis transmission.” 2017. Web. 15 Oct 2019.

Vancouver:

McIntosh AI. Extensions to Bayesian generalized linear mixed effects models for household tuberculosis transmission. [Internet] [Doctoral dissertation]. Boston University; 2017. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/2144/22451.

Council of Science Editors:

McIntosh AI. Extensions to Bayesian generalized linear mixed effects models for household tuberculosis transmission. [Doctoral Dissertation]. Boston University; 2017. Available from: http://hdl.handle.net/2144/22451


University of California – Berkeley

12. Marchand, Philippe. Statistical Methods for the Detection and Space-Time Monitoring of DNA Markers in the Pollen Cloud.

Degree: Environmental Science, Policy, & Management, 2013, University of California – Berkeley

 The analysis of pollen grains finds applications in fields as diverse as allergology, paleoecology, apiculture and forensics. In contrast with morphological identification methods that require… (more)

Subjects/Keywords: Environmental science; Ecology; Biostatistics; Dilution assay; Genetics; Hierarchical Bayesian model; Individual-based model; Pollination

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APA (6th Edition):

Marchand, P. (2013). Statistical Methods for the Detection and Space-Time Monitoring of DNA Markers in the Pollen Cloud. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/8ps0w87q

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):

Marchand, Philippe. “Statistical Methods for the Detection and Space-Time Monitoring of DNA Markers in the Pollen Cloud.” 2013. Thesis, University of California – Berkeley. Accessed October 15, 2019. http://www.escholarship.org/uc/item/8ps0w87q.

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

MLA Handbook (7th Edition):

Marchand, Philippe. “Statistical Methods for the Detection and Space-Time Monitoring of DNA Markers in the Pollen Cloud.” 2013. Web. 15 Oct 2019.

Vancouver:

Marchand P. Statistical Methods for the Detection and Space-Time Monitoring of DNA Markers in the Pollen Cloud. [Internet] [Thesis]. University of California – Berkeley; 2013. [cited 2019 Oct 15]. Available from: http://www.escholarship.org/uc/item/8ps0w87q.

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

Council of Science Editors:

Marchand P. Statistical Methods for the Detection and Space-Time Monitoring of DNA Markers in the Pollen Cloud. [Thesis]. University of California – Berkeley; 2013. Available from: http://www.escholarship.org/uc/item/8ps0w87q

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


University of California – Irvine

13. Hu, Lechuan. Modeling Connectivity in Multi-trial Brain Signals.

Degree: Statistics, 2018, University of California – Irvine

 The hippocampus is critical to memory consolidation. To study the underlying neuronal mechanisms of hippocampus in sequential memory, we consider an experiment recording multi-trial local… (more)

Subjects/Keywords: Statistics; Bayesian hierarchical vector autoregressive model; Brain effective connectivity; Multivariate time series; Vector autoregressive model

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APA (6th Edition):

Hu, L. (2018). Modeling Connectivity in Multi-trial Brain Signals. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/9vm3h315

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):

Hu, Lechuan. “Modeling Connectivity in Multi-trial Brain Signals.” 2018. Thesis, University of California – Irvine. Accessed October 15, 2019. http://www.escholarship.org/uc/item/9vm3h315.

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

MLA Handbook (7th Edition):

Hu, Lechuan. “Modeling Connectivity in Multi-trial Brain Signals.” 2018. Web. 15 Oct 2019.

Vancouver:

Hu L. Modeling Connectivity in Multi-trial Brain Signals. [Internet] [Thesis]. University of California – Irvine; 2018. [cited 2019 Oct 15]. Available from: http://www.escholarship.org/uc/item/9vm3h315.

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

Council of Science Editors:

Hu L. Modeling Connectivity in Multi-trial Brain Signals. [Thesis]. University of California – Irvine; 2018. Available from: http://www.escholarship.org/uc/item/9vm3h315

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


Virginia Tech

14. Chen, Yang. Robust Prediction of Large Spatio-Temporal Datasets.

Degree: MS, Computer Science, 2013, Virginia Tech

 This thesis describes a robust and efficient design of Student-t based Robust Spatio-Temporal Prediction, namely, St-RSTP, to provide estimation based on observations over spatio-temporal neighbors.… (more)

Subjects/Keywords: Robust Prediction; Expectation Propagation; Student's t Model; Bayesian Hierarchical Model; Spatio-Temporal Process

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APA (6th Edition):

Chen, Y. (2013). Robust Prediction of Large Spatio-Temporal Datasets. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/23098

Chicago Manual of Style (16th Edition):

Chen, Yang. “Robust Prediction of Large Spatio-Temporal Datasets.” 2013. Masters Thesis, Virginia Tech. Accessed October 15, 2019. http://hdl.handle.net/10919/23098.

MLA Handbook (7th Edition):

Chen, Yang. “Robust Prediction of Large Spatio-Temporal Datasets.” 2013. Web. 15 Oct 2019.

Vancouver:

Chen Y. Robust Prediction of Large Spatio-Temporal Datasets. [Internet] [Masters thesis]. Virginia Tech; 2013. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/10919/23098.

Council of Science Editors:

Chen Y. Robust Prediction of Large Spatio-Temporal Datasets. [Masters Thesis]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/23098


University of Minnesota

15. Wei, Peng. Network-based mixture models for genomic data.

Degree: PhD, Biostatistics, 2009, University of Minnesota

 A common task in genomic studies is to identify genes satisfying certain conditions, such as differentially expressed genes between normal and tumor tissues or regulatory… (more)

Subjects/Keywords: Bayesian hierarchical model; Gene Network; Genomics; Markov random field; Mixture model; Systems Biology; Biostatistics

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APA (6th Edition):

Wei, P. (2009). Network-based mixture models for genomic data. (Doctoral Dissertation). University of Minnesota. Retrieved from http://purl.umn.edu/54991

Chicago Manual of Style (16th Edition):

Wei, Peng. “Network-based mixture models for genomic data.” 2009. Doctoral Dissertation, University of Minnesota. Accessed October 15, 2019. http://purl.umn.edu/54991.

MLA Handbook (7th Edition):

Wei, Peng. “Network-based mixture models for genomic data.” 2009. Web. 15 Oct 2019.

Vancouver:

Wei P. Network-based mixture models for genomic data. [Internet] [Doctoral dissertation]. University of Minnesota; 2009. [cited 2019 Oct 15]. Available from: http://purl.umn.edu/54991.

Council of Science Editors:

Wei P. Network-based mixture models for genomic data. [Doctoral Dissertation]. University of Minnesota; 2009. Available from: http://purl.umn.edu/54991


Texas A&M University

16. Zhang, Lin. Application of Bayesian Hierarchical Models in Genetic Data Analysis.

Degree: 2012, Texas A&M University

 Genetic data analysis has been capturing a lot of attentions for understanding the mechanism of the development and progressing of diseases like cancers, and is… (more)

Subjects/Keywords: covariance estimation; feature selection; graphical network modeling; genetic data analysis; Bayesian hierarchical model

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APA (6th Edition):

Zhang, L. (2012). Application of Bayesian Hierarchical Models in Genetic Data Analysis. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/148056

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):

Zhang, Lin. “Application of Bayesian Hierarchical Models in Genetic Data Analysis.” 2012. Thesis, Texas A&M University. Accessed October 15, 2019. http://hdl.handle.net/1969.1/148056.

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

MLA Handbook (7th Edition):

Zhang, Lin. “Application of Bayesian Hierarchical Models in Genetic Data Analysis.” 2012. Web. 15 Oct 2019.

Vancouver:

Zhang L. Application of Bayesian Hierarchical Models in Genetic Data Analysis. [Internet] [Thesis]. Texas A&M University; 2012. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1969.1/148056.

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

Council of Science Editors:

Zhang L. Application of Bayesian Hierarchical Models in Genetic Data Analysis. [Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/148056

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


The Ohio State University

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

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 15, 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. 15 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 15]. 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


University of Georgia

18. Bhat, Sanath Govinda. Learning driver preferences for freeway merging using multitask irl.

Degree: MS, Computer Science, 2017, University of Georgia

 Most automobile manufacturers today have invested heavily in the research and design of implementing autonomy in their cars. One important and challenging problem faced by… (more)

Subjects/Keywords: Inverse Reinforcement Learning; Hierarchical Bayesian Model; Multitask; Highway Merging; NGSIM; Likelihood Weighting

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APA (6th Edition):

Bhat, S. G. (2017). Learning driver preferences for freeway merging using multitask irl. (Masters Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/37273

Chicago Manual of Style (16th Edition):

Bhat, Sanath Govinda. “Learning driver preferences for freeway merging using multitask irl.” 2017. Masters Thesis, University of Georgia. Accessed October 15, 2019. http://hdl.handle.net/10724/37273.

MLA Handbook (7th Edition):

Bhat, Sanath Govinda. “Learning driver preferences for freeway merging using multitask irl.” 2017. Web. 15 Oct 2019.

Vancouver:

Bhat SG. Learning driver preferences for freeway merging using multitask irl. [Internet] [Masters thesis]. University of Georgia; 2017. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/10724/37273.

Council of Science Editors:

Bhat SG. Learning driver preferences for freeway merging using multitask irl. [Masters Thesis]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/37273


University of Georgia

19. Bhat, Sanath Govinda. Learning driver preferences for freeway merging using multitask irl.

Degree: MS, Computer Science, 2017, University of Georgia

 Most automobile manufacturers today have invested heavily in the research and design of implementing autonomy in their cars. One important and challenging problem faced by… (more)

Subjects/Keywords: Inverse Reinforcement Learning; Hierarchical Bayesian Model; Multitask; Highway Merging; NGSIM; Likelihood Weighting

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

APA (6th Edition):

Bhat, S. G. (2017). Learning driver preferences for freeway merging using multitask irl. (Masters Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/37116

Chicago Manual of Style (16th Edition):

Bhat, Sanath Govinda. “Learning driver preferences for freeway merging using multitask irl.” 2017. Masters Thesis, University of Georgia. Accessed October 15, 2019. http://hdl.handle.net/10724/37116.

MLA Handbook (7th Edition):

Bhat, Sanath Govinda. “Learning driver preferences for freeway merging using multitask irl.” 2017. Web. 15 Oct 2019.

Vancouver:

Bhat SG. Learning driver preferences for freeway merging using multitask irl. [Internet] [Masters thesis]. University of Georgia; 2017. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/10724/37116.

Council of Science Editors:

Bhat SG. Learning driver preferences for freeway merging using multitask irl. [Masters Thesis]. University of Georgia; 2017. Available from: http://hdl.handle.net/10724/37116


Duke University

20. Luo, Kaixuan. Modeling Nuclease Digestion Data to Predict the Dynamics of Genome-wide Transcription Factor Occupancy .

Degree: 2016, Duke University

  Identifying and deciphering the complex regulatory information embedded in the genome is critical to our understanding of biology and the etiology of complex diseases.… (more)

Subjects/Keywords: Bioinformatics; Genetics; Bayesian hierarchical model; ChIP-seq; DNase-seq; gene regulation; MNase-seq; transcription factors

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APA (6th Edition):

Luo, K. (2016). Modeling Nuclease Digestion Data to Predict the Dynamics of Genome-wide Transcription Factor Occupancy . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/14351

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

Chicago Manual of Style (16th Edition):

Luo, Kaixuan. “Modeling Nuclease Digestion Data to Predict the Dynamics of Genome-wide Transcription Factor Occupancy .” 2016. Thesis, Duke University. Accessed October 15, 2019. http://hdl.handle.net/10161/14351.

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

MLA Handbook (7th Edition):

Luo, Kaixuan. “Modeling Nuclease Digestion Data to Predict the Dynamics of Genome-wide Transcription Factor Occupancy .” 2016. Web. 15 Oct 2019.

Vancouver:

Luo K. Modeling Nuclease Digestion Data to Predict the Dynamics of Genome-wide Transcription Factor Occupancy . [Internet] [Thesis]. Duke University; 2016. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/10161/14351.

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

Council of Science Editors:

Luo K. Modeling Nuclease Digestion Data to Predict the Dynamics of Genome-wide Transcription Factor Occupancy . [Thesis]. Duke University; 2016. Available from: http://hdl.handle.net/10161/14351

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


University of Waterloo

21. Wu, Margaret. A Latent Health Factor Model for Estimating Estuarine Ecosystem Health.

Degree: 2009, University of Waterloo

 Assessment of the “health” of an ecosystem is often of great interest to those interested in monitoring and conservation of ecosystems. Traditionally, scientists have quantified… (more)

Subjects/Keywords: Bayesian hierarchical model; estuarine ecosystem health

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APA (6th Edition):

Wu, M. (2009). A Latent Health Factor Model for Estimating Estuarine Ecosystem Health. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/4425

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):

Wu, Margaret. “A Latent Health Factor Model for Estimating Estuarine Ecosystem Health.” 2009. Thesis, University of Waterloo. Accessed October 15, 2019. http://hdl.handle.net/10012/4425.

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

MLA Handbook (7th Edition):

Wu, Margaret. “A Latent Health Factor Model for Estimating Estuarine Ecosystem Health.” 2009. Web. 15 Oct 2019.

Vancouver:

Wu M. A Latent Health Factor Model for Estimating Estuarine Ecosystem Health. [Internet] [Thesis]. University of Waterloo; 2009. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/10012/4425.

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

Council of Science Editors:

Wu M. A Latent Health Factor Model for Estimating Estuarine Ecosystem Health. [Thesis]. University of Waterloo; 2009. Available from: http://hdl.handle.net/10012/4425

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


University of Kentucky

22. Ellis, Amanda R. ACCOUNTING FOR MATCHING UNCERTAINTY IN PHOTOGRAPHIC IDENTIFICATION STUDIES OF WILD ANIMALS.

Degree: 2018, University of Kentucky

 I consider statistical modelling of data gathered by photographic identification in mark-recapture studies and propose a new method that incorporates the inherent uncertainty of photographic… (more)

Subjects/Keywords: Mark-Recapture; Photographic Identification; Bayesian Analysis; Hierarchical Model; Applied Statistics; Statistical Models

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APA (6th Edition):

Ellis, A. R. (2018). ACCOUNTING FOR MATCHING UNCERTAINTY IN PHOTOGRAPHIC IDENTIFICATION STUDIES OF WILD ANIMALS. (Doctoral Dissertation). University of Kentucky. Retrieved from https://uknowledge.uky.edu/statistics_etds/31

Chicago Manual of Style (16th Edition):

Ellis, Amanda R. “ACCOUNTING FOR MATCHING UNCERTAINTY IN PHOTOGRAPHIC IDENTIFICATION STUDIES OF WILD ANIMALS.” 2018. Doctoral Dissertation, University of Kentucky. Accessed October 15, 2019. https://uknowledge.uky.edu/statistics_etds/31.

MLA Handbook (7th Edition):

Ellis, Amanda R. “ACCOUNTING FOR MATCHING UNCERTAINTY IN PHOTOGRAPHIC IDENTIFICATION STUDIES OF WILD ANIMALS.” 2018. Web. 15 Oct 2019.

Vancouver:

Ellis AR. ACCOUNTING FOR MATCHING UNCERTAINTY IN PHOTOGRAPHIC IDENTIFICATION STUDIES OF WILD ANIMALS. [Internet] [Doctoral dissertation]. University of Kentucky; 2018. [cited 2019 Oct 15]. Available from: https://uknowledge.uky.edu/statistics_etds/31.

Council of Science Editors:

Ellis AR. ACCOUNTING FOR MATCHING UNCERTAINTY IN PHOTOGRAPHIC IDENTIFICATION STUDIES OF WILD ANIMALS. [Doctoral Dissertation]. University of Kentucky; 2018. Available from: https://uknowledge.uky.edu/statistics_etds/31


Duquesne University

23. Jordan, Joseph Patrick. Bayesian Hierarchical Modeling for Longitudinal Frequency Data.

Degree: MS, Computational Mathematics, 2005, Duquesne University

 This research is to develop a longitudinal frequency model for data collected regularly for several individuals over an extended time period. This model must recognize… (more)

Subjects/Keywords: Bayesian; Hierarchical Model; Longitudinal Frequency Data

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APA (6th Edition):

Jordan, J. P. (2005). Bayesian Hierarchical Modeling for Longitudinal Frequency Data. (Masters Thesis). Duquesne University. Retrieved from https://dsc.duq.edu/etd/711

Chicago Manual of Style (16th Edition):

Jordan, Joseph Patrick. “Bayesian Hierarchical Modeling for Longitudinal Frequency Data.” 2005. Masters Thesis, Duquesne University. Accessed October 15, 2019. https://dsc.duq.edu/etd/711.

MLA Handbook (7th Edition):

Jordan, Joseph Patrick. “Bayesian Hierarchical Modeling for Longitudinal Frequency Data.” 2005. Web. 15 Oct 2019.

Vancouver:

Jordan JP. Bayesian Hierarchical Modeling for Longitudinal Frequency Data. [Internet] [Masters thesis]. Duquesne University; 2005. [cited 2019 Oct 15]. Available from: https://dsc.duq.edu/etd/711.

Council of Science Editors:

Jordan JP. Bayesian Hierarchical Modeling for Longitudinal Frequency Data. [Masters Thesis]. Duquesne University; 2005. Available from: https://dsc.duq.edu/etd/711


Brigham Young University

24. Page, Garritt L. Using Box-Scores to Determine a Position's Contribution to Winning Basketball Games.

Degree: MS, 2005, Brigham Young University

 Basketball is a sport that has become increasingly popular world-wide. At the professional level it is a game in which each of the five positions… (more)

Subjects/Keywords: Bayesian Hierarchical Model; Statistics and Probability

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APA (6th Edition):

Page, G. L. (2005). Using Box-Scores to Determine a Position's Contribution to Winning Basketball Games. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=1655&context=etd

Chicago Manual of Style (16th Edition):

Page, Garritt L. “Using Box-Scores to Determine a Position's Contribution to Winning Basketball Games.” 2005. Masters Thesis, Brigham Young University. Accessed October 15, 2019. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=1655&context=etd.

MLA Handbook (7th Edition):

Page, Garritt L. “Using Box-Scores to Determine a Position's Contribution to Winning Basketball Games.” 2005. Web. 15 Oct 2019.

Vancouver:

Page GL. Using Box-Scores to Determine a Position's Contribution to Winning Basketball Games. [Internet] [Masters thesis]. Brigham Young University; 2005. [cited 2019 Oct 15]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=1655&context=etd.

Council of Science Editors:

Page GL. Using Box-Scores to Determine a Position's Contribution to Winning Basketball Games. [Masters Thesis]. Brigham Young University; 2005. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=1655&context=etd


University of Kentucky

25. Roualdes, Edward A. New Results in ell_1 Penalized Regression.

Degree: 2015, University of Kentucky

 Here we consider penalized regression methods, and extend on the results surrounding the l1 norm penalty. We address a more recent development that generalizes previous… (more)

Subjects/Keywords: linear model; penalized regression; Bayesian analysis; Hierarchical Models; Applied Statistics; Statistical Models

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

APA (6th Edition):

Roualdes, E. A. (2015). New Results in ell_1 Penalized Regression. (Doctoral Dissertation). University of Kentucky. Retrieved from https://uknowledge.uky.edu/statistics_etds/13

Chicago Manual of Style (16th Edition):

Roualdes, Edward A. “New Results in ell_1 Penalized Regression.” 2015. Doctoral Dissertation, University of Kentucky. Accessed October 15, 2019. https://uknowledge.uky.edu/statistics_etds/13.

MLA Handbook (7th Edition):

Roualdes, Edward A. “New Results in ell_1 Penalized Regression.” 2015. Web. 15 Oct 2019.

Vancouver:

Roualdes EA. New Results in ell_1 Penalized Regression. [Internet] [Doctoral dissertation]. University of Kentucky; 2015. [cited 2019 Oct 15]. Available from: https://uknowledge.uky.edu/statistics_etds/13.

Council of Science Editors:

Roualdes EA. New Results in ell_1 Penalized Regression. [Doctoral Dissertation]. University of Kentucky; 2015. Available from: https://uknowledge.uky.edu/statistics_etds/13


Queensland University of Technology

26. Tran, Thu Trung. Bayesian model estimation and comparison for longitudinal categorical data.

Degree: 2008, Queensland University of Technology

 In this thesis, we address issues of model estimation for longitudinal categorical data and of model selection for these data with missing covariates. Longitudinal survey… (more)

Subjects/Keywords: longitudinal data analysis; generalized linear models; Bayesian hierarchical models; Bayesian model choice; Bayes factors; deviance information criterion; missing data

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

APA (6th Edition):

Tran, T. T. (2008). Bayesian model estimation and comparison for longitudinal categorical data. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/19240/

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):

Tran, Thu Trung. “Bayesian model estimation and comparison for longitudinal categorical data.” 2008. Thesis, Queensland University of Technology. Accessed October 15, 2019. https://eprints.qut.edu.au/19240/.

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

MLA Handbook (7th Edition):

Tran, Thu Trung. “Bayesian model estimation and comparison for longitudinal categorical data.” 2008. Web. 15 Oct 2019.

Vancouver:

Tran TT. Bayesian model estimation and comparison for longitudinal categorical data. [Internet] [Thesis]. Queensland University of Technology; 2008. [cited 2019 Oct 15]. Available from: https://eprints.qut.edu.au/19240/.

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

Council of Science Editors:

Tran TT. Bayesian model estimation and comparison for longitudinal categorical data. [Thesis]. Queensland University of Technology; 2008. Available from: https://eprints.qut.edu.au/19240/

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


McMaster University

27. Bai, Yu Qing. Longitudinal Analysis to Assess the Impact of Method of Delivery on Postpartum Outcomes: The Ontario Mother and Infant Study (TOMIS) III.

Degree: MSc, 2011, McMaster University

Postpartum depression has become a major public health concern for women within a specific time period after delivery. Depression is possibly associated with some… (more)

Subjects/Keywords: The Ontario Mother and Infant Study; generalized estimating equations; generalized linear mixed effect model; hierarchical generalized linear model; Bayesian hierarchical model; Biostatistics; Longitudinal Data Analysis and Time Series; Biostatistics

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

APA (6th Edition):

Bai, Y. Q. (2011). Longitudinal Analysis to Assess the Impact of Method of Delivery on Postpartum Outcomes: The Ontario Mother and Infant Study (TOMIS) III. (Masters Thesis). McMaster University. Retrieved from http://hdl.handle.net/11375/11402

Chicago Manual of Style (16th Edition):

Bai, Yu Qing. “Longitudinal Analysis to Assess the Impact of Method of Delivery on Postpartum Outcomes: The Ontario Mother and Infant Study (TOMIS) III.” 2011. Masters Thesis, McMaster University. Accessed October 15, 2019. http://hdl.handle.net/11375/11402.

MLA Handbook (7th Edition):

Bai, Yu Qing. “Longitudinal Analysis to Assess the Impact of Method of Delivery on Postpartum Outcomes: The Ontario Mother and Infant Study (TOMIS) III.” 2011. Web. 15 Oct 2019.

Vancouver:

Bai YQ. Longitudinal Analysis to Assess the Impact of Method of Delivery on Postpartum Outcomes: The Ontario Mother and Infant Study (TOMIS) III. [Internet] [Masters thesis]. McMaster University; 2011. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/11375/11402.

Council of Science Editors:

Bai YQ. Longitudinal Analysis to Assess the Impact of Method of Delivery on Postpartum Outcomes: The Ontario Mother and Infant Study (TOMIS) III. [Masters Thesis]. McMaster University; 2011. Available from: http://hdl.handle.net/11375/11402


The Ohio State University

28. Han, Gang. Modeling The Output From Computer Experiments Having Quantitative And Qualitative Input Variables And Its Applications.

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

  Complex computer models have extensive usage in scientific and engineering studies. Because the number of computer runs is typically limited, statistical models are used… (more)

Subjects/Keywords: Statistics; Gaussian stochastic process model; Product Gaussian correlation; Hierarchical Bayesian model; Root mean squared prediction error.

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APA (6th Edition):

Han, G. (2008). Modeling The Output From Computer Experiments Having Quantitative And Qualitative Input Variables And Its Applications. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1228326460

Chicago Manual of Style (16th Edition):

Han, Gang. “Modeling The Output From Computer Experiments Having Quantitative And Qualitative Input Variables And Its Applications.” 2008. Doctoral Dissertation, The Ohio State University. Accessed October 15, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1228326460.

MLA Handbook (7th Edition):

Han, Gang. “Modeling The Output From Computer Experiments Having Quantitative And Qualitative Input Variables And Its Applications.” 2008. Web. 15 Oct 2019.

Vancouver:

Han G. Modeling The Output From Computer Experiments Having Quantitative And Qualitative Input Variables And Its Applications. [Internet] [Doctoral dissertation]. The Ohio State University; 2008. [cited 2019 Oct 15]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1228326460.

Council of Science Editors:

Han G. Modeling The Output From Computer Experiments Having Quantitative And Qualitative Input Variables And Its Applications. [Doctoral Dissertation]. The Ohio State University; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1228326460


University of Washington

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

Degree: PhD, 2013, University of Washington

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

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

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APA (6th Edition):

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

Chicago Manual of Style (16th Edition):

Wheldon, Mark Christopher. “Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data.” 2013. Doctoral Dissertation, University of Washington. Accessed October 15, 2019. http://hdl.handle.net/1773/22813.

MLA Handbook (7th Edition):

Wheldon, Mark Christopher. “Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data.” 2013. Web. 15 Oct 2019.

Vancouver:

Wheldon MC. Bayesian Population Reconstruction: A Method for Estimating Age- and Sex-specific Vital Rates and Population Counts with Uncertainty from Fragmentary Data. [Internet] [Doctoral dissertation]. University of Washington; 2013. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1773/22813.

Council of Science Editors:

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


George Mason University

30. Yan, Yongping. Bayesian Hierarchical Point-Pattern-Based Intensity Model in Prediction of Highway Losses .

Degree: 2013, George Mason University

 Traditional spatial-temporal models either use separable models to separate spatial processes from temporal processes, which often results in a loss of information, or use nonseparable… (more)

Subjects/Keywords: Statistics; Public health; Bayesian Hierarchical Model; Expectation Maximization; Finite Mixture model; Highway losses; Poisson point process; Spatio-temporal

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APA (6th Edition):

Yan, Y. (2013). Bayesian Hierarchical Point-Pattern-Based Intensity Model in Prediction of Highway Losses . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/8754

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):

Yan, Yongping. “Bayesian Hierarchical Point-Pattern-Based Intensity Model in Prediction of Highway Losses .” 2013. Thesis, George Mason University. Accessed October 15, 2019. http://hdl.handle.net/1920/8754.

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

MLA Handbook (7th Edition):

Yan, Yongping. “Bayesian Hierarchical Point-Pattern-Based Intensity Model in Prediction of Highway Losses .” 2013. Web. 15 Oct 2019.

Vancouver:

Yan Y. Bayesian Hierarchical Point-Pattern-Based Intensity Model in Prediction of Highway Losses . [Internet] [Thesis]. George Mason University; 2013. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1920/8754.

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

Council of Science Editors:

Yan Y. Bayesian Hierarchical Point-Pattern-Based Intensity Model in Prediction of Highway Losses . [Thesis]. George Mason University; 2013. Available from: http://hdl.handle.net/1920/8754

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

[1] [2] [3] [4]

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