Evolution Review Of BayesCalc, A Mathematica™ Package for doing Bayesian Calculations

  • Paul Desmedt
  • Ignace Lemahieu
  • K. Thielemans
Conference paper
Part of the Fundamental Theories of Physics book series (FTPH, volume 70)


The application of Bayesian probability theory requires only a few rules: the sum rule, the product rule and the marginalization procedure. However, in practice Bayesian computations can become tedious. The package BayesCalc implements the rules governing Bayesian probability theory in a Mathematica framework. Consequently BayesCalc can help introduce Bayesian theory to newcomers and facilitate computations for regular Bayesians.

The implemented rules enable the calculation of posterior probabilities from probabilistic relations. The main rules are the product and marginalization rule.

The previous version of BayesCalc dealt with symbolic calculations. Unfortunately, problems arise with some symbolic operations, especially integrations. To overcome this problem, numerical versions of many operations were added to the package. Some additional utilities are offered: decision theory, hypothesis testing and discrete ranges for parameters.


Posterior Probability Decision Theory Product Rule Nuisance Parameter Symbolic Calculation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Paul Desmedt
    • 1
  • Ignace Lemahieu
    • 1
  • K. Thielemans
    • 2
  1. 1.Department of Electronics and Information SystemsUniversity of GhentGhentBelgium
  2. 2.Instituut voor Theoretische FysicaKatholieke Universiteit LeuvenLeuvenBelgium

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