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Bayesian Decision Making: Theory and Examples

The introductory part to Bayesian Decision Making deals with four basic tasks:

  • modelling (simulation),
  • estimation,
  • prediction
  • and control.

These tasks, used for single input - single output cases, are simple enough to demonstrate clearly the basis of the whole theory and, on the other hande, they are mostly needed and used in the practice. The basic theory results to algorithms which are implemented in Octave (open source clone of MATLAB). The examples are available to download in the svn repository.


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SVN repository (with password only):


24.03.2015 - 12:28