User:Timothee Flutre/Notebook/Postdoc/2011/11/16

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** "Advanced Data Analysis from an Elementary Point of View" by Cosma Shalizi (free online [http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ book])
** "Advanced Data Analysis from an Elementary Point of View" by Cosma Shalizi (free online [http://www.stat.cmu.edu/~cshalizi/ADAfaEPoV/ book])
** "A First Course in Bayesian Statistical Methods" by Peter Hoff ([http://www.amazon.com/gp/product/0387922997 book])
** "A First Course in Bayesian Statistical Methods" by Peter Hoff ([http://www.amazon.com/gp/product/0387922997 book])
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** "Bayesian Data Analysis" by Andrew Gelman (free online [http://www.stat.columbia.edu/~gelman/book/slides slides])
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** "Bayesian Data Analysis" by Andrew Gelman (free online [http://www.stat.columbia.edu/~gelman/book/slides slides], [http://www.amazon.com/dp/1439840954 book])
* '''mathematical aspects''':
* '''mathematical aspects''':
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** "Intro to Linear Algebra" by Gilbert Strang
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** "Introduction to Linear Algebra" by Gilbert Strang (free online [http://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/ videos], [http://www.amazon.com/dp/0980232716 book])
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** "Multivariate Calculus" by Magnus and Neudecker
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** "Matrix Differential Calculus with Applications in Statistics and Econometrics" by Magnus and Neudecker (free online [http://www.janmagnus.nl/misc/mdc2007-3rdedition pdf], [http://www.amazon.com/dp/047198633X book])
* '''practical, computational aspects''':
* '''practical, computational aspects''':
** "Exploratory Data Analysis with R" by Jennifer Bryan (free online [http://www.stat.ubc.ca/~jenny/STAT545A/2012-lectures/ course])
** "Exploratory Data Analysis with R" by Jennifer Bryan (free online [http://www.stat.ubc.ca/~jenny/STAT545A/2012-lectures/ course])
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** editor: Emacs
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** "Tutorial on Big Data with Python" by Marcel Caraciolo (free online Python [https://github.com/marcelcaraciolo/big-data-tutorial notebooks])
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** interpreted languages: R, Python and others (Julia?)
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** interpreted languages: obviously [http://openwetware.org/wiki/User:Timothee_Flutre/Notebook/Postdoc/2011/11/07 R], but more and more Python ([http://www.scipy.org/ SciPy] for NumPy, IPython, Matplotlib, and pandas, but also [http://scikit-learn.org/ scikit-learn] and [http://statsmodels.sourceforge.net/ statsmodels]), as well as others (Julia?)
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** C/C++: GSL, Armadillo, Eigen, Rcpp
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** C/C++: [http://en.wikipedia.org/wiki/GNU_Scientific_Library GSL], [http://en.wikipedia.org/wiki/Armadillo_%28C++_library%29 Armadillo], [http://en.wikipedia.org/wiki/Eigen_(C%2B%2B_library) Eigen], [http://www.rcpp.org/ Rcpp], [http://mc-stan.org/ Stan]
 +
** editor: [https://openwetware.org/wiki/User:Timothee_Flutre/Notebook/Postdoc/2012/07/25 Emacs]
* '''visualizing, plotting''':
* '''visualizing, plotting''':
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** "Visualizing uncertainty about the future" by Spiegelhalter, et al. (Science 2011, [http://dx.doi.org/10.1126/science.1191181 DOI])
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** "Visualizing uncertainty about the future" by Spiegelhalter et al. (Science 2011, [http://dx.doi.org/10.1126/science.1191181 DOI])
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** "Let's practice what we preach: turning tables into graphs": Gelman et al (The American Statistician 2002, [http://dx.doi.org/10.1198/000313002317572790 DOI])
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** "Let's practice what we preach: turning tables into graphs" by Gelman et al. (The American Statistician 2002, [http://dx.doi.org/10.1198/000313002317572790 DOI])
* '''philosophy, history''':
* '''philosophy, history''':
-
** Christian Hennig
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** "Mathematical Models and Reality: A Constructivist Perspective" by Christian Hennig (Foundations of Science 2007, [http://dx.doi.org/10.1007/s10699-009-9167-x DOI])
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** Andrew Gelman and Cosma Shalizi
+
** "Philosophy and the practice of Bayesian statistics" by Andrew Gelman and Cosma Shalizi (British Journal of Mathematical and Statistical Psychology 2013, [http://dx.doi.org/10.1111/j.2044-8317.2011.02037.x DOI])
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** Christian Robert
+
** "Des spécificités de l’approche bayésienne et de ses justifications en statistique inférentielle" by Christian Robert (chapitre 2013, free online [http://hal.archives-ouvertes.fr/docs/00/87/01/24/PDF/Bayes.pdf pdf])
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 +
* '''classics''':
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** [https://www.ceremade.dauphine.fr/~xian/M2classics.html list] from Christian Robert
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Revision as of 21:25, 29 November 2013

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About statistical modeling

  • great courses:
    • "Advanced Data Analysis from an Elementary Point of View" by Cosma Shalizi (free online book)
    • "A First Course in Bayesian Statistical Methods" by Peter Hoff (book)
    • "Bayesian Data Analysis" by Andrew Gelman (free online slides, book)
  • mathematical aspects:
    • "Introduction to Linear Algebra" by Gilbert Strang (free online videos, book)
    • "Matrix Differential Calculus with Applications in Statistics and Econometrics" by Magnus and Neudecker (free online pdf, book)
  • practical, computational aspects:
    • "Exploratory Data Analysis with R" by Jennifer Bryan (free online course)
    • "Tutorial on Big Data with Python" by Marcel Caraciolo (free online Python notebooks)
    • interpreted languages: obviously R, but more and more Python (SciPy for NumPy, IPython, Matplotlib, and pandas, but also scikit-learn and statsmodels), as well as others (Julia?)
    • C/C++: GSL, Armadillo, Eigen, Rcpp, Stan
    • editor: Emacs
  • visualizing, plotting:
    • "Visualizing uncertainty about the future" by Spiegelhalter et al. (Science 2011, DOI)
    • "Let's practice what we preach: turning tables into graphs" by Gelman et al. (The American Statistician 2002, DOI)
  • philosophy, history:
    • "Mathematical Models and Reality: A Constructivist Perspective" by Christian Hennig (Foundations of Science 2007, DOI)
    • "Philosophy and the practice of Bayesian statistics" by Andrew Gelman and Cosma Shalizi (British Journal of Mathematical and Statistical Psychology 2013, DOI)
    • "Des spécificités de l’approche bayésienne et de ses justifications en statistique inférentielle" by Christian Robert (chapitre 2013, free online pdf)
  • classics:
    • list from Christian Robert


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