Prof.  Luca Amendola


Institut für Theoretische Physik -- Universität Heidelberg


Philosophenweg 16 -- D-69120 Heidelberg -- Germany

Tel: +49-6221-549-407 -- Fax: +49-6221-549-333

Sprechstunde: After my lectures
and by appointment Tuesday 11.00 - 12.00 a.m. (other times also possible)





 Bayesian Statistical Methods in Physics and Astrophysics

Winter Semester 2012/13

   The course is an introduction to Bayesian statistical methods in Physics and Astrophysics
    CREDITS: 3 (oral exam on the program or, alternatively, seminar on some selected topic; exam by appointment; the detailed program will be communicated at the end of the course)   

Program

  - Introduction to probability: definitions, joint and disjoint probability, conditional prob.,
     moments, transf. of variables, Binomial, Poissonian, Gaussian, multivariate prob., examples
  - Estimation of parameters
     Max. Lik. estimators
     Bayes' theorem
     Likelihood method, conf. regions, marginalization
     examples
  - From the likeliood to the Fisher matrix
     Fisher manipulation
     Figure of Merit
     examples
  - General Fisher matrix for gaussian variables
  - Two-point statistics
    correlation function and power spectrum
    higher-order statistics
  - Fisher matrix for the power spectrum
    examples from Euclid
  - Fisher matrix for weak lensing
  - Principal component analysis
    Model selection, evidence
    robustness


   NOTE: Course begins on October 16th, 2012 (more info)

   classes at 14:15-16:00 Philosophenweg 12, kHS

  
  
   Calendar (to be confirmed):
   16.10
   23.10
   30.10
   06.11
   13.11
   20.11
   27.11   (lecture by V. Marra: MonteCarlo methods)
   04.12   no lecture
   11.12   no lecture
   18.12
   08.01
   15.01

  

    Suggested texts:

    Lecture notes version 5/2012
    L. Amendola and S. Tsujikawa, Dark Energy, Theory and Observations, Cambridge University Press, 2010,
   chapters 3 and 13
   R. Trotta,Bayes in the sky: Bayesian inference and model selection in cosmology,
   P. Gregory, Bayesian Logical Data Analysis for the Physical Sciences, Cambridge University Press

 
   
 


   
   


 

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