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You searched for subject:(Statistical Inference). Showing records 1 – 30 of 233 total matches.

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Columbia University

1. Resa Juárez, María de los Angeles. Essays on Matching and Weighting for Causal Inference in Observational Studies.

Degree: 2017, Columbia University

 This thesis consists of three papers on matching and weighting methods for causal inference. The first paper conducts a Monte Carlo simulation study to evaluate… (more)

Subjects/Keywords: Statistics; Inference; Statistical matching; Probabilities

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

APA (6th Edition):

Resa Juárez, M. d. l. A. (2017). Essays on Matching and Weighting for Causal Inference in Observational Studies. (Doctoral Dissertation). Columbia University. Retrieved from https://doi.org/10.7916/D8959W4H

Chicago Manual of Style (16th Edition):

Resa Juárez, María de los Angeles. “Essays on Matching and Weighting for Causal Inference in Observational Studies.” 2017. Doctoral Dissertation, Columbia University. Accessed October 16, 2019. https://doi.org/10.7916/D8959W4H.

MLA Handbook (7th Edition):

Resa Juárez, María de los Angeles. “Essays on Matching and Weighting for Causal Inference in Observational Studies.” 2017. Web. 16 Oct 2019.

Vancouver:

Resa Juárez MdlA. Essays on Matching and Weighting for Causal Inference in Observational Studies. [Internet] [Doctoral dissertation]. Columbia University; 2017. [cited 2019 Oct 16]. Available from: https://doi.org/10.7916/D8959W4H.

Council of Science Editors:

Resa Juárez MdlA. Essays on Matching and Weighting for Causal Inference in Observational Studies. [Doctoral Dissertation]. Columbia University; 2017. Available from: https://doi.org/10.7916/D8959W4H


University of Illinois – Urbana-Champaign

2. Xu, Jiaming. Statistical inference in networks: fundamental limits and efficient algorithms.

Degree: PhD, 1200, 2015, University of Illinois – Urbana-Champaign

 Today witnesses an explosion of data coming from various types of networks such as online social networks and biological networks. The goal of this thesis… (more)

Subjects/Keywords: Community detection; Networks; Statistical inference

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APA (6th Edition):

Xu, J. (2015). Statistical inference in networks: fundamental limits and efficient algorithms. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/72799

Chicago Manual of Style (16th Edition):

Xu, Jiaming. “Statistical inference in networks: fundamental limits and efficient algorithms.” 2015. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed October 16, 2019. http://hdl.handle.net/2142/72799.

MLA Handbook (7th Edition):

Xu, Jiaming. “Statistical inference in networks: fundamental limits and efficient algorithms.” 2015. Web. 16 Oct 2019.

Vancouver:

Xu J. Statistical inference in networks: fundamental limits and efficient algorithms. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2015. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/2142/72799.

Council of Science Editors:

Xu J. Statistical inference in networks: fundamental limits and efficient algorithms. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/72799


University of New Orleans

3. Nguyen, Trang. Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking.

Degree: MS, Electrical Engineering, 2003, University of New Orleans

 Nonlinear filtering is certainly very important in estimation since most real-world problems are nonlinear. Recently a considerable progress in the nonlinear filtering theory has been… (more)

Subjects/Keywords: statistical inference

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APA (6th Edition):

Nguyen, T. (2003). Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking. (Thesis). University of New Orleans. Retrieved from https://scholarworks.uno.edu/td/20

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):

Nguyen, Trang. “Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking.” 2003. Thesis, University of New Orleans. Accessed October 16, 2019. https://scholarworks.uno.edu/td/20.

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

MLA Handbook (7th Edition):

Nguyen, Trang. “Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking.” 2003. Web. 16 Oct 2019.

Vancouver:

Nguyen T. Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking. [Internet] [Thesis]. University of New Orleans; 2003. [cited 2019 Oct 16]. Available from: https://scholarworks.uno.edu/td/20.

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

Council of Science Editors:

Nguyen T. Comparison of Sampling-Based Algorithms for Multisensor Distributed Target Tracking. [Thesis]. University of New Orleans; 2003. Available from: https://scholarworks.uno.edu/td/20

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


Princeton University

4. Zhao, Tianqi. Statistical Inference for Big Data .

Degree: PhD, 2017, Princeton University

 This dissertation develops novel inferential methods and theory for assessing uncertainty of modern statistical procedures unique to big data analysis. In particular, we mainly focus… (more)

Subjects/Keywords: Big Data; Statistical Inference

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APA (6th Edition):

Zhao, T. (2017). Statistical Inference for Big Data . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp017d278w62w

Chicago Manual of Style (16th Edition):

Zhao, Tianqi. “Statistical Inference for Big Data .” 2017. Doctoral Dissertation, Princeton University. Accessed October 16, 2019. http://arks.princeton.edu/ark:/88435/dsp017d278w62w.

MLA Handbook (7th Edition):

Zhao, Tianqi. “Statistical Inference for Big Data .” 2017. Web. 16 Oct 2019.

Vancouver:

Zhao T. Statistical Inference for Big Data . [Internet] [Doctoral dissertation]. Princeton University; 2017. [cited 2019 Oct 16]. Available from: http://arks.princeton.edu/ark:/88435/dsp017d278w62w.

Council of Science Editors:

Zhao T. Statistical Inference for Big Data . [Doctoral Dissertation]. Princeton University; 2017. Available from: http://arks.princeton.edu/ark:/88435/dsp017d278w62w


Texas A&M University

5. Knight, Jason Matthew. Optimal Model-Based Approaches for Predictive Inference in Biology.

Degree: 2015, Texas A&M University

 Predictive modeling of the dynamic, multivariate, non-linear, stochastic systems of biology is a difficult enterprise. High throughput measurement techniques are enabling new approaches to computational… (more)

Subjects/Keywords: computational biology; predictive inference; statistical modeling; bioinformatics

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APA (6th Edition):

Knight, J. M. (2015). Optimal Model-Based Approaches for Predictive Inference in Biology. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/155131

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):

Knight, Jason Matthew. “Optimal Model-Based Approaches for Predictive Inference in Biology.” 2015. Thesis, Texas A&M University. Accessed October 16, 2019. http://hdl.handle.net/1969.1/155131.

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

MLA Handbook (7th Edition):

Knight, Jason Matthew. “Optimal Model-Based Approaches for Predictive Inference in Biology.” 2015. Web. 16 Oct 2019.

Vancouver:

Knight JM. Optimal Model-Based Approaches for Predictive Inference in Biology. [Internet] [Thesis]. Texas A&M University; 2015. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/1969.1/155131.

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

Council of Science Editors:

Knight JM. Optimal Model-Based Approaches for Predictive Inference in Biology. [Thesis]. Texas A&M University; 2015. Available from: http://hdl.handle.net/1969.1/155131

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

6. Miles, Alexander S. Mathematical Modelling and Statistical Inference from Immune Response Data.

Degree: 2017, RIAN

 A hallmark of the adaptive immune response is the proliferation of pathogen-specific lymphocytes that leave in their wake a long lived population of cells that… (more)

Subjects/Keywords: Mathematical Modelling; Statistical Inference; Immune Response Data

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APA (6th Edition):

Miles, A. S. (2017). Mathematical Modelling and Statistical Inference from Immune Response Data. (Thesis). RIAN. Retrieved from http://eprints.maynoothuniversity.ie/8850/

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):

Miles, Alexander S. “Mathematical Modelling and Statistical Inference from Immune Response Data.” 2017. Thesis, RIAN. Accessed October 16, 2019. http://eprints.maynoothuniversity.ie/8850/.

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

MLA Handbook (7th Edition):

Miles, Alexander S. “Mathematical Modelling and Statistical Inference from Immune Response Data.” 2017. Web. 16 Oct 2019.

Vancouver:

Miles AS. Mathematical Modelling and Statistical Inference from Immune Response Data. [Internet] [Thesis]. RIAN; 2017. [cited 2019 Oct 16]. Available from: http://eprints.maynoothuniversity.ie/8850/.

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

Council of Science Editors:

Miles AS. Mathematical Modelling and Statistical Inference from Immune Response Data. [Thesis]. RIAN; 2017. Available from: http://eprints.maynoothuniversity.ie/8850/

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

7. Epstein, Caroline G. Correcting for the Dependence Structure in Social Networks.

Degree: 2014, Johns Hopkins University

 The use of social network data has recently become increasingly prevalent in social science research and in clinical fields. While some researchers deliberately exploit the… (more)

Subjects/Keywords: social networks; network; dependence; statistical inference

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APA (6th Edition):

Epstein, C. G. (2014). Correcting for the Dependence Structure in Social Networks. (Thesis). Johns Hopkins University. Retrieved from http://jhir.library.jhu.edu/handle/1774.2/37250

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):

Epstein, Caroline G. “Correcting for the Dependence Structure in Social Networks.” 2014. Thesis, Johns Hopkins University. Accessed October 16, 2019. http://jhir.library.jhu.edu/handle/1774.2/37250.

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

MLA Handbook (7th Edition):

Epstein, Caroline G. “Correcting for the Dependence Structure in Social Networks.” 2014. Web. 16 Oct 2019.

Vancouver:

Epstein CG. Correcting for the Dependence Structure in Social Networks. [Internet] [Thesis]. Johns Hopkins University; 2014. [cited 2019 Oct 16]. Available from: http://jhir.library.jhu.edu/handle/1774.2/37250.

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

Council of Science Editors:

Epstein CG. Correcting for the Dependence Structure in Social Networks. [Thesis]. Johns Hopkins University; 2014. Available from: http://jhir.library.jhu.edu/handle/1774.2/37250

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


University of Edinburgh

8. Schnoerr, David Benjamin. Approximation methods and inference for stochastic biochemical kinetics.

Degree: PhD, 2016, University of Edinburgh

 Recent experiments have shown the fundamental role that random fluctuations play in many chemical systems in living cells, such as gene regulatory networks. Mathematical models… (more)

Subjects/Keywords: 519.2; stochastic processes; approximation methods; statistical inference

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APA (6th Edition):

Schnoerr, D. B. (2016). Approximation methods and inference for stochastic biochemical kinetics. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/25444

Chicago Manual of Style (16th Edition):

Schnoerr, David Benjamin. “Approximation methods and inference for stochastic biochemical kinetics.” 2016. Doctoral Dissertation, University of Edinburgh. Accessed October 16, 2019. http://hdl.handle.net/1842/25444.

MLA Handbook (7th Edition):

Schnoerr, David Benjamin. “Approximation methods and inference for stochastic biochemical kinetics.” 2016. Web. 16 Oct 2019.

Vancouver:

Schnoerr DB. Approximation methods and inference for stochastic biochemical kinetics. [Internet] [Doctoral dissertation]. University of Edinburgh; 2016. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/1842/25444.

Council of Science Editors:

Schnoerr DB. Approximation methods and inference for stochastic biochemical kinetics. [Doctoral Dissertation]. University of Edinburgh; 2016. Available from: http://hdl.handle.net/1842/25444


University of Akron

9. Ravali, Yeluri. BALLWORLD: A FRAMEWORK FOR LEARNING STATISTICAL INFERENCE AND STREAM PROCESSING.

Degree: MSin Engineering, Computer Engineering, 2017, University of Akron

 This thesis presents a framework called \emph{BallWorld} thatenables the exploration and understanding of topics in the areas of statistical inference and data science. Many fundamentalconcepts… (more)

Subjects/Keywords: Computer Engineering; Statistical Inference, Stream Processing

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APA (6th Edition):

Ravali, Y. (2017). BALLWORLD: A FRAMEWORK FOR LEARNING STATISTICAL INFERENCE AND STREAM PROCESSING. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1498769835817335

Chicago Manual of Style (16th Edition):

Ravali, Yeluri. “BALLWORLD: A FRAMEWORK FOR LEARNING STATISTICAL INFERENCE AND STREAM PROCESSING.” 2017. Masters Thesis, University of Akron. Accessed October 16, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1498769835817335.

MLA Handbook (7th Edition):

Ravali, Yeluri. “BALLWORLD: A FRAMEWORK FOR LEARNING STATISTICAL INFERENCE AND STREAM PROCESSING.” 2017. Web. 16 Oct 2019.

Vancouver:

Ravali Y. BALLWORLD: A FRAMEWORK FOR LEARNING STATISTICAL INFERENCE AND STREAM PROCESSING. [Internet] [Masters thesis]. University of Akron; 2017. [cited 2019 Oct 16]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1498769835817335.

Council of Science Editors:

Ravali Y. BALLWORLD: A FRAMEWORK FOR LEARNING STATISTICAL INFERENCE AND STREAM PROCESSING. [Masters Thesis]. University of Akron; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1498769835817335


University of New South Wales

10. Liu, Xianghang. New Algorithms for Graphical Models and Their Applications in Learning.

Degree: Computer Science & Engineering, 2015, University of New South Wales

 Probabilistic graphical models bring together graph theory and probability theory in a powerful formalism for multivariate statistical modelling. Since many machine learning problems involve the… (more)

Subjects/Keywords: statistical inference; machine learning; graphical model

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APA (6th Edition):

Liu, X. (2015). New Algorithms for Graphical Models and Their Applications in Learning. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Liu, Xianghang. “New Algorithms for Graphical Models and Their Applications in Learning.” 2015. Doctoral Dissertation, University of New South Wales. Accessed October 16, 2019. http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true.

MLA Handbook (7th Edition):

Liu, Xianghang. “New Algorithms for Graphical Models and Their Applications in Learning.” 2015. Web. 16 Oct 2019.

Vancouver:

Liu X. New Algorithms for Graphical Models and Their Applications in Learning. [Internet] [Doctoral dissertation]. University of New South Wales; 2015. [cited 2019 Oct 16]. Available from: http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true.

Council of Science Editors:

Liu X. New Algorithms for Graphical Models and Their Applications in Learning. [Doctoral Dissertation]. University of New South Wales; 2015. Available from: http://handle.unsw.edu.au/1959.4/55080 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:36494/SOURCE02?view=true


University of Waterloo

11. Granade, Christopher E. Characterization, Verification and Control for Large Quantum Systems.

Degree: 2015, University of Waterloo

 Quantum information processing offers potential improvements to a wide range of computing endevaors, including cryptography, chemistry simulations and machine learning. The development of practical quantum… (more)

Subjects/Keywords: quantum information; statistical inference; optimal control theory; error correction; genetic algorithms; information locality; statistical inference; nitrogen-vacancy centers; neutron interferometry

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APA (6th Edition):

Granade, C. E. (2015). Characterization, Verification and Control for Large Quantum Systems. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/9217

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):

Granade, Christopher E. “Characterization, Verification and Control for Large Quantum Systems.” 2015. Thesis, University of Waterloo. Accessed October 16, 2019. http://hdl.handle.net/10012/9217.

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

MLA Handbook (7th Edition):

Granade, Christopher E. “Characterization, Verification and Control for Large Quantum Systems.” 2015. Web. 16 Oct 2019.

Vancouver:

Granade CE. Characterization, Verification and Control for Large Quantum Systems. [Internet] [Thesis]. University of Waterloo; 2015. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/10012/9217.

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

Council of Science Editors:

Granade CE. Characterization, Verification and Control for Large Quantum Systems. [Thesis]. University of Waterloo; 2015. Available from: http://hdl.handle.net/10012/9217

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


University of Arkansas

12. Zhang, Huarui. Monte Carlo Methods in Bayesian Inference: Theory, Methods and Applications.

Degree: MS, 2016, University of Arkansas

  Monte Carlo methods are becoming more and more popular in statistics due to the fast development of efficient computing technologies. One of the major… (more)

Subjects/Keywords: Pure sciences; Bayesian inference; Efficient computing technologies; Monte carlo; Applied Statistics; Statistical Methodology; Statistical Theory

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APA (6th Edition):

Zhang, H. (2016). Monte Carlo Methods in Bayesian Inference: Theory, Methods and Applications. (Masters Thesis). University of Arkansas. Retrieved from https://scholarworks.uark.edu/etd/1796

Chicago Manual of Style (16th Edition):

Zhang, Huarui. “Monte Carlo Methods in Bayesian Inference: Theory, Methods and Applications.” 2016. Masters Thesis, University of Arkansas. Accessed October 16, 2019. https://scholarworks.uark.edu/etd/1796.

MLA Handbook (7th Edition):

Zhang, Huarui. “Monte Carlo Methods in Bayesian Inference: Theory, Methods and Applications.” 2016. Web. 16 Oct 2019.

Vancouver:

Zhang H. Monte Carlo Methods in Bayesian Inference: Theory, Methods and Applications. [Internet] [Masters thesis]. University of Arkansas; 2016. [cited 2019 Oct 16]. Available from: https://scholarworks.uark.edu/etd/1796.

Council of Science Editors:

Zhang H. Monte Carlo Methods in Bayesian Inference: Theory, Methods and Applications. [Masters Thesis]. University of Arkansas; 2016. Available from: https://scholarworks.uark.edu/etd/1796

13. Tamminen, Toni. Models and Methods for Bayesian Object Matching.

Degree: 2005, Helsinki University of Technology

This thesis is concerned with a central aspect of computer vision, the object matching problem. In object matching the aim is to detect and precisely… (more)

Subjects/Keywords: statistical image analysis; object recognition; Monte Carlo simulation; Bayesian inference

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APA (6th Edition):

Tamminen, T. (2005). Models and Methods for Bayesian Object Matching. (Thesis). Helsinki University of Technology. Retrieved from http://lib.tkk.fi/Diss/2005/isbn951227907X/

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):

Tamminen, Toni. “Models and Methods for Bayesian Object Matching.” 2005. Thesis, Helsinki University of Technology. Accessed October 16, 2019. http://lib.tkk.fi/Diss/2005/isbn951227907X/.

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

MLA Handbook (7th Edition):

Tamminen, Toni. “Models and Methods for Bayesian Object Matching.” 2005. Web. 16 Oct 2019.

Vancouver:

Tamminen T. Models and Methods for Bayesian Object Matching. [Internet] [Thesis]. Helsinki University of Technology; 2005. [cited 2019 Oct 16]. Available from: http://lib.tkk.fi/Diss/2005/isbn951227907X/.

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

Council of Science Editors:

Tamminen T. Models and Methods for Bayesian Object Matching. [Thesis]. Helsinki University of Technology; 2005. Available from: http://lib.tkk.fi/Diss/2005/isbn951227907X/

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


Texas A&M University

14. Asava-Vallobh, Norabajra. Essays on Efficiency Analysis.

Degree: 2010, Texas A&M University

 This dissertation consists of four essays which investigate efficiency analysis, especially when non-discretionary inputs exist. A new approach of the multi-stage Data Envelopment Analysis (DEA)… (more)

Subjects/Keywords: Efficiency; Data envelopment analysis; DEA; Non-discretionary inputs; Statistical inference

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APA (6th Edition):

Asava-Vallobh, N. (2010). Essays on Efficiency Analysis. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-643

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):

Asava-Vallobh, Norabajra. “Essays on Efficiency Analysis.” 2010. Thesis, Texas A&M University. Accessed October 16, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-643.

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

MLA Handbook (7th Edition):

Asava-Vallobh, Norabajra. “Essays on Efficiency Analysis.” 2010. Web. 16 Oct 2019.

Vancouver:

Asava-Vallobh N. Essays on Efficiency Analysis. [Internet] [Thesis]. Texas A&M University; 2010. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-643.

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

Council of Science Editors:

Asava-Vallobh N. Essays on Efficiency Analysis. [Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-643

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

15. Vinod Kumar. Statistical inference in linear regression model using improved estimators; -.

Degree: Stastistics, 2015, Maharshi Dayanand University

None

Bibliography p. 147 - 154

Advisors/Committee Members: Dube, Madhulika.

Subjects/Keywords: improved estimators; inference; regression; Statistical

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APA (6th Edition):

Kumar, V. (2015). Statistical inference in linear regression model using improved estimators; -. (Thesis). Maharshi Dayanand University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/38752

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):

Kumar, Vinod. “Statistical inference in linear regression model using improved estimators; -.” 2015. Thesis, Maharshi Dayanand University. Accessed October 16, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/38752.

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

MLA Handbook (7th Edition):

Kumar, Vinod. “Statistical inference in linear regression model using improved estimators; -.” 2015. Web. 16 Oct 2019.

Vancouver:

Kumar V. Statistical inference in linear regression model using improved estimators; -. [Internet] [Thesis]. Maharshi Dayanand University; 2015. [cited 2019 Oct 16]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/38752.

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

Council of Science Editors:

Kumar V. Statistical inference in linear regression model using improved estimators; -. [Thesis]. Maharshi Dayanand University; 2015. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/38752

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

16. Narayana, P. Statistical inference in sets of linear regression models; -.

Degree: Statistics, 2002, Sri Venkateswara University

None

Bibliography p.190-206

Advisors/Committee Members: Balasiddamuni, P.

Subjects/Keywords: linear regression; Statistical inference; Statistics

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

APA (6th Edition):

Narayana, P. (2002). Statistical inference in sets of linear regression models; -. (Thesis). Sri Venkateswara University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/53264

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):

Narayana, P. “Statistical inference in sets of linear regression models; -.” 2002. Thesis, Sri Venkateswara University. Accessed October 16, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/53264.

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

MLA Handbook (7th Edition):

Narayana, P. “Statistical inference in sets of linear regression models; -.” 2002. Web. 16 Oct 2019.

Vancouver:

Narayana P. Statistical inference in sets of linear regression models; -. [Internet] [Thesis]. Sri Venkateswara University; 2002. [cited 2019 Oct 16]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/53264.

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

Council of Science Editors:

Narayana P. Statistical inference in sets of linear regression models; -. [Thesis]. Sri Venkateswara University; 2002. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/53264

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


Georgia Tech

17. Coder, Ryan Daniel. Multi-Objective Design of Small Telescopes and Their Application to Space Object Characterization.

Degree: PhD, Aerospace Engineering, 2016, Georgia Tech

 Recognizing the increasingly congested and contested nature of space, this thesis contends that the fusion of small aperture, autonomous telescopes with Bayesian inference techniques can… (more)

Subjects/Keywords: multi-objective design; small telescopes; light curve inversion; statistical inference

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APA (6th Edition):

Coder, R. D. (2016). Multi-Objective Design of Small Telescopes and Their Application to Space Object Characterization. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55567

Chicago Manual of Style (16th Edition):

Coder, Ryan Daniel. “Multi-Objective Design of Small Telescopes and Their Application to Space Object Characterization.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 16, 2019. http://hdl.handle.net/1853/55567.

MLA Handbook (7th Edition):

Coder, Ryan Daniel. “Multi-Objective Design of Small Telescopes and Their Application to Space Object Characterization.” 2016. Web. 16 Oct 2019.

Vancouver:

Coder RD. Multi-Objective Design of Small Telescopes and Their Application to Space Object Characterization. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/1853/55567.

Council of Science Editors:

Coder RD. Multi-Objective Design of Small Telescopes and Their Application to Space Object Characterization. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/55567


Hong Kong University of Science and Technology

18. Li, Dong. Statistical inference for some threshold models.

Degree: 2010, Hong Kong University of Science and Technology

 This thesis considers three important threshold time series models: threshold moving-average (TMA) models, threshold double autoregressive (TDAR) models and multiple-regime threshold autoregressive (MTAR) models. For… (more)

Subjects/Keywords: Time-series analysis  – Statistical methods; Autoregression (Statistics); Inference

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APA (6th Edition):

Li, D. (2010). Statistical inference for some threshold models. (Thesis). Hong Kong University of Science and Technology. Retrieved from https://doi.org/10.14711/thesis-b1129752 ; http://repository.ust.hk/ir/bitstream/1783.1-7082/1/th_redirect.html

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

Chicago Manual of Style (16th Edition):

Li, Dong. “Statistical inference for some threshold models.” 2010. Thesis, Hong Kong University of Science and Technology. Accessed October 16, 2019. https://doi.org/10.14711/thesis-b1129752 ; http://repository.ust.hk/ir/bitstream/1783.1-7082/1/th_redirect.html.

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

MLA Handbook (7th Edition):

Li, Dong. “Statistical inference for some threshold models.” 2010. Web. 16 Oct 2019.

Vancouver:

Li D. Statistical inference for some threshold models. [Internet] [Thesis]. Hong Kong University of Science and Technology; 2010. [cited 2019 Oct 16]. Available from: https://doi.org/10.14711/thesis-b1129752 ; http://repository.ust.hk/ir/bitstream/1783.1-7082/1/th_redirect.html.

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

Council of Science Editors:

Li D. Statistical inference for some threshold models. [Thesis]. Hong Kong University of Science and Technology; 2010. Available from: https://doi.org/10.14711/thesis-b1129752 ; http://repository.ust.hk/ir/bitstream/1783.1-7082/1/th_redirect.html

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


Michigan Technological University

19. Shi, Lufeng. USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS.

Degree: PhD, Department of Electrical and Computer Engineering, 2014, Michigan Technological University

  Sensor networks have been an active research area in the past decade due to the variety of their applications. Many research studies have been… (more)

Subjects/Keywords: Graphical Model; Statistical Inference; Target Tracking; Wireless Sensor Network; Computer Engineering

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

APA (6th Edition):

Shi, L. (2014). USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS. (Doctoral Dissertation). Michigan Technological University. Retrieved from http://digitalcommons.mtu.edu/etds/752

Chicago Manual of Style (16th Edition):

Shi, Lufeng. “USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS.” 2014. Doctoral Dissertation, Michigan Technological University. Accessed October 16, 2019. http://digitalcommons.mtu.edu/etds/752.

MLA Handbook (7th Edition):

Shi, Lufeng. “USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS.” 2014. Web. 16 Oct 2019.

Vancouver:

Shi L. USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS. [Internet] [Doctoral dissertation]. Michigan Technological University; 2014. [cited 2019 Oct 16]. Available from: http://digitalcommons.mtu.edu/etds/752.

Council of Science Editors:

Shi L. USING PROBABILISTIC GRAPHICAL MODELS TO DRAW INFERENCES IN SENSOR NETWORKS WITH TRACKING APPLICATIONS. [Doctoral Dissertation]. Michigan Technological University; 2014. Available from: http://digitalcommons.mtu.edu/etds/752


University of California – Berkeley

20. Hu, Jane. Learning from others through testimony and statistics.

Degree: Psychology, 2014, University of California – Berkeley

 In learning about the world, children have at least two types of information available to them: information they learn from their personal experiences, and information… (more)

Subjects/Keywords: Developmental psychology; Cognitive psychology; Social psychology; social cognition; statistical inference

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APA (6th Edition):

Hu, J. (2014). Learning from others through testimony and statistics. (Thesis). University of California – Berkeley. Retrieved from http://www.escholarship.org/uc/item/11m7q656

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, Jane. “Learning from others through testimony and statistics.” 2014. Thesis, University of California – Berkeley. Accessed October 16, 2019. http://www.escholarship.org/uc/item/11m7q656.

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

MLA Handbook (7th Edition):

Hu, Jane. “Learning from others through testimony and statistics.” 2014. Web. 16 Oct 2019.

Vancouver:

Hu J. Learning from others through testimony and statistics. [Internet] [Thesis]. University of California – Berkeley; 2014. [cited 2019 Oct 16]. Available from: http://www.escholarship.org/uc/item/11m7q656.

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

Council of Science Editors:

Hu J. Learning from others through testimony and statistics. [Thesis]. University of California – Berkeley; 2014. Available from: http://www.escholarship.org/uc/item/11m7q656

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


University of California – San Diego

21. Suresh, Ananda Theertha. Statistical Inference over Large Domains.

Degree: Electrical Engineering (Communication Theory and Systems), 2016, University of California – San Diego

 Motivated by diverse applications in ecology, genetics, and language modeling, researchers in learning, computer science, and information theory have recently studied several fundamental statistical questions… (more)

Subjects/Keywords: Electrical engineering; Information science; Good-Turing estimators; Large Domain; Statistical Inference

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APA (6th Edition):

Suresh, A. T. (2016). Statistical Inference over Large Domains. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/6vr8w9bq

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):

Suresh, Ananda Theertha. “Statistical Inference over Large Domains.” 2016. Thesis, University of California – San Diego. Accessed October 16, 2019. http://www.escholarship.org/uc/item/6vr8w9bq.

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

MLA Handbook (7th Edition):

Suresh, Ananda Theertha. “Statistical Inference over Large Domains.” 2016. Web. 16 Oct 2019.

Vancouver:

Suresh AT. Statistical Inference over Large Domains. [Internet] [Thesis]. University of California – San Diego; 2016. [cited 2019 Oct 16]. Available from: http://www.escholarship.org/uc/item/6vr8w9bq.

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

Council of Science Editors:

Suresh AT. Statistical Inference over Large Domains. [Thesis]. University of California – San Diego; 2016. Available from: http://www.escholarship.org/uc/item/6vr8w9bq

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


University of Southern California

22. Lin, Ning. Parameter estimation in second-order stochastic differential equations.

Degree: PhD, Applied Mathematics, 2012, University of Southern California

 While consistency of the maximum likelihood estimator of the unknown parameters in the second-order linear stochastic differential equation driven by Gaussian white noise holds under… (more)

Subjects/Keywords: statistical inference; Gaussian process; maximum likelihood estimation; consistency

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

APA (6th Edition):

Lin, N. (2012). Parameter estimation in second-order stochastic differential equations. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/86412/rec/4911

Chicago Manual of Style (16th Edition):

Lin, Ning. “Parameter estimation in second-order stochastic differential equations.” 2012. Doctoral Dissertation, University of Southern California. Accessed October 16, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/86412/rec/4911.

MLA Handbook (7th Edition):

Lin, Ning. “Parameter estimation in second-order stochastic differential equations.” 2012. Web. 16 Oct 2019.

Vancouver:

Lin N. Parameter estimation in second-order stochastic differential equations. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2019 Oct 16]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/86412/rec/4911.

Council of Science Editors:

Lin N. Parameter estimation in second-order stochastic differential equations. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/86412/rec/4911


University of Southern California

23. Rozgić, Viktor. Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions.

Degree: PhD, Electrical Engineering, 2011, University of Southern California

 In this dissertation we propose contributions that address the problems in behavioral signal processing for small-group interactions from three important perspectives. We propose algorithmic contributions… (more)

Subjects/Keywords: statistical inference; multi-modal signal processing; behavioral signal processing

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

APA (6th Edition):

Rozgić, V. (2011). Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/653978/rec/6042

Chicago Manual of Style (16th Edition):

Rozgić, Viktor. “Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions.” 2011. Doctoral Dissertation, University of Southern California. Accessed October 16, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/653978/rec/6042.

MLA Handbook (7th Edition):

Rozgić, Viktor. “Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions.” 2011. Web. 16 Oct 2019.

Vancouver:

Rozgić V. Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Oct 16]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/653978/rec/6042.

Council of Science Editors:

Rozgić V. Statistical inference for dynamical, interacting multi-object systems with emphasis on human small group interactions. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/653978/rec/6042


Duke University

24. Rasmussen, David Alan. Phylodynamic Methods for Infectious Disease Epidemiology .

Degree: 2014, Duke University

  In this dissertation, I present a general statistical framework for phylodynamic inference that can be used to estimate epidemiological parameters and reconstruct disease dynamics… (more)

Subjects/Keywords: Epidemiology; Statistics; Biology; Coalescent; Dengue; HIV; Infectious disease; Phylodynamics; Statistical inference

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

APA (6th Edition):

Rasmussen, D. A. (2014). Phylodynamic Methods for Infectious Disease Epidemiology . (Thesis). Duke University. Retrieved from http://hdl.handle.net/10161/8701

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):

Rasmussen, David Alan. “Phylodynamic Methods for Infectious Disease Epidemiology .” 2014. Thesis, Duke University. Accessed October 16, 2019. http://hdl.handle.net/10161/8701.

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

MLA Handbook (7th Edition):

Rasmussen, David Alan. “Phylodynamic Methods for Infectious Disease Epidemiology .” 2014. Web. 16 Oct 2019.

Vancouver:

Rasmussen DA. Phylodynamic Methods for Infectious Disease Epidemiology . [Internet] [Thesis]. Duke University; 2014. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/10161/8701.

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

Council of Science Editors:

Rasmussen DA. Phylodynamic Methods for Infectious Disease Epidemiology . [Thesis]. Duke University; 2014. Available from: http://hdl.handle.net/10161/8701

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


Virginia Tech

25. Kim, Jae-yoon. Essays on DSGE Models and Bayesian Estimation.

Degree: PhD, Economics, Science, 2018, Virginia Tech

 This thesis explores the theory and practice of sovereignty. I begin with a conceptual analysis of sovereignty, examining its theological roots in contrast with its… (more)

Subjects/Keywords: Bayesian Inference; Statistical Adequacy; Misspecification Testing; Student's t VAR

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APA (6th Edition):

Kim, J. (2018). Essays on DSGE Models and Bayesian Estimation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83515

Chicago Manual of Style (16th Edition):

Kim, Jae-yoon. “Essays on DSGE Models and Bayesian Estimation.” 2018. Doctoral Dissertation, Virginia Tech. Accessed October 16, 2019. http://hdl.handle.net/10919/83515.

MLA Handbook (7th Edition):

Kim, Jae-yoon. “Essays on DSGE Models and Bayesian Estimation.” 2018. Web. 16 Oct 2019.

Vancouver:

Kim J. Essays on DSGE Models and Bayesian Estimation. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/10919/83515.

Council of Science Editors:

Kim J. Essays on DSGE Models and Bayesian Estimation. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83515


Curtin University of Technology

26. Jiang, Zhenyu. Statistical analysis of genomic data : a new model for class prediction and inference .

Degree: 2011, Curtin University of Technology

 Genomics is a major scientific revolution in this century. High-throughput genomic data provides an opportunity for identifying genes and SNPs (singlenucleotide polymorphism) that are related… (more)

Subjects/Keywords: genomic data; class prediction; class inference; Statistical analysis

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APA (6th Edition):

Jiang, Z. (2011). Statistical analysis of genomic data : a new model for class prediction and inference . (Thesis). Curtin University of Technology. Retrieved from http://hdl.handle.net/20.500.11937/1017

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):

Jiang, Zhenyu. “Statistical analysis of genomic data : a new model for class prediction and inference .” 2011. Thesis, Curtin University of Technology. Accessed October 16, 2019. http://hdl.handle.net/20.500.11937/1017.

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

MLA Handbook (7th Edition):

Jiang, Zhenyu. “Statistical analysis of genomic data : a new model for class prediction and inference .” 2011. Web. 16 Oct 2019.

Vancouver:

Jiang Z. Statistical analysis of genomic data : a new model for class prediction and inference . [Internet] [Thesis]. Curtin University of Technology; 2011. [cited 2019 Oct 16]. Available from: http://hdl.handle.net/20.500.11937/1017.

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

Council of Science Editors:

Jiang Z. Statistical analysis of genomic data : a new model for class prediction and inference . [Thesis]. Curtin University of Technology; 2011. Available from: http://hdl.handle.net/20.500.11937/1017

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


University of Kentucky

27. Burchett, Woodrow. Improving the Computational Efficiency in Bayesian Fitting of Cormack-Jolly-Seber Models with Individual, Continuous, Time-Varying Covariates.

Degree: 2017, University of Kentucky

 The extension of the CJS model to include individual, continuous, time-varying covariates relies on the estimation of covariate values on occasions on which individuals were… (more)

Subjects/Keywords: Mark-recapture; Bayesian Inference; Variational Bayes; Statistical Models

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APA (6th Edition):

Burchett, W. (2017). Improving the Computational Efficiency in Bayesian Fitting of Cormack-Jolly-Seber Models with Individual, Continuous, Time-Varying Covariates. (Doctoral Dissertation). University of Kentucky. Retrieved from https://uknowledge.uky.edu/statistics_etds/27

Chicago Manual of Style (16th Edition):

Burchett, Woodrow. “Improving the Computational Efficiency in Bayesian Fitting of Cormack-Jolly-Seber Models with Individual, Continuous, Time-Varying Covariates.” 2017. Doctoral Dissertation, University of Kentucky. Accessed October 16, 2019. https://uknowledge.uky.edu/statistics_etds/27.

MLA Handbook (7th Edition):

Burchett, Woodrow. “Improving the Computational Efficiency in Bayesian Fitting of Cormack-Jolly-Seber Models with Individual, Continuous, Time-Varying Covariates.” 2017. Web. 16 Oct 2019.

Vancouver:

Burchett W. Improving the Computational Efficiency in Bayesian Fitting of Cormack-Jolly-Seber Models with Individual, Continuous, Time-Varying Covariates. [Internet] [Doctoral dissertation]. University of Kentucky; 2017. [cited 2019 Oct 16]. Available from: https://uknowledge.uky.edu/statistics_etds/27.

Council of Science Editors:

Burchett W. Improving the Computational Efficiency in Bayesian Fitting of Cormack-Jolly-Seber Models with Individual, Continuous, Time-Varying Covariates. [Doctoral Dissertation]. University of Kentucky; 2017. Available from: https://uknowledge.uky.edu/statistics_etds/27


Rochester Institute of Technology

28. Seo, Sujeong. Production Quality for Process Capability with Multiple Characteristics on the Chip Resistor Production.

Degree: MS, 2017, Rochester Institute of Technology

  There are many journal papers about process capability indices with multiple characteristics in certain manufacturing assemblies including Cp, Cpk, Cpu, and Cpl. However, all… (more)

Subjects/Keywords: Process capability index; Production management; Quality control; Quality engineering; Statistical inference

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

APA (6th Edition):

Seo, S. (2017). Production Quality for Process Capability with Multiple Characteristics on the Chip Resistor Production. (Masters Thesis). Rochester Institute of Technology. Retrieved from https://scholarworks.rit.edu/theses/9576

Chicago Manual of Style (16th Edition):

Seo, Sujeong. “Production Quality for Process Capability with Multiple Characteristics on the Chip Resistor Production.” 2017. Masters Thesis, Rochester Institute of Technology. Accessed October 16, 2019. https://scholarworks.rit.edu/theses/9576.

MLA Handbook (7th Edition):

Seo, Sujeong. “Production Quality for Process Capability with Multiple Characteristics on the Chip Resistor Production.” 2017. Web. 16 Oct 2019.

Vancouver:

Seo S. Production Quality for Process Capability with Multiple Characteristics on the Chip Resistor Production. [Internet] [Masters thesis]. Rochester Institute of Technology; 2017. [cited 2019 Oct 16]. Available from: https://scholarworks.rit.edu/theses/9576.

Council of Science Editors:

Seo S. Production Quality for Process Capability with Multiple Characteristics on the Chip Resistor Production. [Masters Thesis]. Rochester Institute of Technology; 2017. Available from: https://scholarworks.rit.edu/theses/9576


University of Florida

29. Martinez Nino, Carlos Alberto. Studies on Statistical Genomics to Improve the Estimation of Allele Frequencies, Breed Composition, Variance Components, and Prediction of Additive Genetic Values.

Degree: PhD, Animal Sciences, 2017, University of Florida

 This dissertation is devoted to the development of novel statistical methods for point estimation and prediction that incorporate genomic information into a series of relevant… (more)

Subjects/Keywords: bayesian-inference  – genetics  – genomic-selection  – graphical-models  – prediction  – statistical-genomics

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

APA (6th Edition):

Martinez Nino, C. A. (2017). Studies on Statistical Genomics to Improve the Estimation of Allele Frequencies, Breed Composition, Variance Components, and Prediction of Additive Genetic Values. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0051012

Chicago Manual of Style (16th Edition):

Martinez Nino, Carlos Alberto. “Studies on Statistical Genomics to Improve the Estimation of Allele Frequencies, Breed Composition, Variance Components, and Prediction of Additive Genetic Values.” 2017. Doctoral Dissertation, University of Florida. Accessed October 16, 2019. http://ufdc.ufl.edu/UFE0051012.

MLA Handbook (7th Edition):

Martinez Nino, Carlos Alberto. “Studies on Statistical Genomics to Improve the Estimation of Allele Frequencies, Breed Composition, Variance Components, and Prediction of Additive Genetic Values.” 2017. Web. 16 Oct 2019.

Vancouver:

Martinez Nino CA. Studies on Statistical Genomics to Improve the Estimation of Allele Frequencies, Breed Composition, Variance Components, and Prediction of Additive Genetic Values. [Internet] [Doctoral dissertation]. University of Florida; 2017. [cited 2019 Oct 16]. Available from: http://ufdc.ufl.edu/UFE0051012.

Council of Science Editors:

Martinez Nino CA. Studies on Statistical Genomics to Improve the Estimation of Allele Frequencies, Breed Composition, Variance Components, and Prediction of Additive Genetic Values. [Doctoral Dissertation]. University of Florida; 2017. Available from: http://ufdc.ufl.edu/UFE0051012


University of Notre Dame

30. Alonso Faruck Morcos Gonzalez. Multiscale Protein Networks: Interactions, Two Component Systems and Kinetics</h1>.

Degree: PhD, Computer Science and Engineering, 2010, University of Notre Dame

  Living organisms are driven by molecular machines called proteins. To understand the molecular mechanisms of the cell, it is not enough to understand individual… (more)

Subjects/Keywords: statistical inference; protein structure; two component systems; molecular interactions; conformational space

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APA (6th Edition):

Gonzalez, A. F. M. (2010). Multiscale Protein Networks: Interactions, Two Component Systems and Kinetics</h1>. (Doctoral Dissertation). University of Notre Dame. Retrieved from https://curate.nd.edu/show/k0698625s02

Chicago Manual of Style (16th Edition):

Gonzalez, Alonso Faruck Morcos. “Multiscale Protein Networks: Interactions, Two Component Systems and Kinetics</h1>.” 2010. Doctoral Dissertation, University of Notre Dame. Accessed October 16, 2019. https://curate.nd.edu/show/k0698625s02.

MLA Handbook (7th Edition):

Gonzalez, Alonso Faruck Morcos. “Multiscale Protein Networks: Interactions, Two Component Systems and Kinetics</h1>.” 2010. Web. 16 Oct 2019.

Vancouver:

Gonzalez AFM. Multiscale Protein Networks: Interactions, Two Component Systems and Kinetics</h1>. [Internet] [Doctoral dissertation]. University of Notre Dame; 2010. [cited 2019 Oct 16]. Available from: https://curate.nd.edu/show/k0698625s02.

Council of Science Editors:

Gonzalez AFM. Multiscale Protein Networks: Interactions, Two Component Systems and Kinetics</h1>. [Doctoral Dissertation]. University of Notre Dame; 2010. Available from: https://curate.nd.edu/show/k0698625s02

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