Bayesian statistics

Results: 3999



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11Posterior predictive checks can and should be Bayesian: Comment on Gelman and Shalizi, Philosophy and the practice of Bayesian statistics

Posterior predictive checks can and should be Bayesian: Comment on Gelman and Shalizi, Philosophy and the practice of Bayesian statistics

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Source URL: www.indiana.edu

- Date: 2013-01-18 10:07:57
    12Bayesian Statistics Then and Now

    Bayesian Statistics Then and Now

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    Source URL: www.stat.columbia.edu

    - Date: 2010-11-25 10:00:05
      13Bayesian Analysis or Evidence Based Statistics D.A.S. Fraser Department of Statistics, University of Toronto, Canada M5S 3G3 Introduction The original Bayes proposal leads to likelihood and confidence for many simple exa

      Bayesian Analysis or Evidence Based Statistics D.A.S. Fraser Department of Statistics, University of Toronto, Canada M5S 3G3 Introduction The original Bayes proposal leads to likelihood and confidence for many simple exa

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      Source URL: fisher.utstat.toronto.edu

      - Date: 2012-04-02 13:00:54
        14Submitted to the Annals of Applied Statistics arXiv: BAYESIAN INFERENCE FOR NMR SPECTROSCOPY WITH APPLICATIONS TO CHEMICAL QUANTIFICATION By Andrew Gordon Wilson∗ , Yuting Wu∗ , Daniel J. Holland∗ ,

        Submitted to the Annals of Applied Statistics arXiv: BAYESIAN INFERENCE FOR NMR SPECTROSCOPY WITH APPLICATIONS TO CHEMICAL QUANTIFICATION By Andrew Gordon Wilson∗ , Yuting Wu∗ , Daniel J. Holland∗ ,

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        Source URL: www.cs.cmu.edu

        - Date: 2014-09-11 09:47:08
          15Bayes or likelihood: Convergence or Divergence Organizer: D.A.S. Fraser What model information is appropriate for the Bayesian paradigm? Don Fraser Department of Statistics

          Bayes or likelihood: Convergence or Divergence Organizer: D.A.S. Fraser What model information is appropriate for the Bayesian paradigm? Don Fraser Department of Statistics

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          Source URL: fisher.utstat.toronto.edu

          - Date: 2012-04-02 13:00:54
            16Electronic Journal of Statistics Vol–1074 ISSN: DOI: EJS485 Dynamics of Bayesian updating with

            Electronic Journal of Statistics Vol–1074 ISSN: DOI: EJS485 Dynamics of Bayesian updating with

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            Source URL: apophenia.wdfiles.com

            - Date: 2012-09-17 05:38:43
              17Bayes or likelihood: Convergence or Divergence Organizer: D.A.S. Fraser What model information is appropriate for the Bayesian paradigm? Don Fraser Department of Statistics

              Bayes or likelihood: Convergence or Divergence Organizer: D.A.S. Fraser What model information is appropriate for the Bayesian paradigm? Don Fraser Department of Statistics

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              Source URL: fisher.utstat.toronto.edu

              - Date: 2012-04-02 13:00:54
                18Examples of Bayesian Statistical Thinking in Neuroscience Rob E. Kass Department of Statistics, Machine Learning Department, and Center for the Neural Basis of Cognition Carnegie Mellon University

                Examples of Bayesian Statistical Thinking in Neuroscience Rob E. Kass Department of Statistics, Machine Learning Department, and Center for the Neural Basis of Cognition Carnegie Mellon University

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                Source URL: www.icts.uci.edu

                - Date: 2015-03-09 19:18:28
                  19Philosophy and the practice of Bayesian statistics Andrew Gelman Department of Statistics and Department of Political Science, Columbia University Cosma Rohilla Shalizi Statistics Department, Carnegie Mellon University

                  Philosophy and the practice of Bayesian statistics Andrew Gelman Department of Statistics and Department of Political Science, Columbia University Cosma Rohilla Shalizi Statistics Department, Carnegie Mellon University

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                  Source URL: www.stat.columbia.edu

                  - Date: 2011-06-27 21:25:48
                    20Portfolio construction with Bayesian GARCH forecasts Wolfgang Polasek and Momtchil Pojarliev Institute of Statistics and Econometrics University of Basel

                    Portfolio construction with Bayesian GARCH forecasts Wolfgang Polasek and Momtchil Pojarliev Institute of Statistics and Econometrics University of Basel

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                    Source URL: www.istfin.eco.usi.ch

                    - Date: 2009-01-27 08:16:58