Abstract
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.
supported by a grant from IWONL, Brusseles, Belgium
research associate with the NFWO, Brussels, Belgium
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© 1996 Kluwer Academic Publishers
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Desmedt, P., Lemahieu, I., Thielemans, K. (1996). Evolution Review Of BayesCalc, A Mathematica™ Package for doing Bayesian Calculations. In: Skilling, J., Sibisi, S. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 70. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0107-0_14
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DOI: https://doi.org/10.1007/978-94-009-0107-0_14
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