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Updating Probabilities
AIP conference proceedings · 2006 · Vol. 872 · pp. 31–42
Ariel Caticha✉(University at Albany, State University of New York)Adom Giffin(University at Albany, State University of New York)
Abstract
We show that Skilling's method of induction leads to a unique general theory of inductive inference, the method of Maximum relative Entropy (ME). The main tool for updating probabilities is the logarithmic relative entropy; other entropies such as those of Renyi or Tsallis are ruled out. We also show that Bayes updating is a special case of ME updating and thus, that the two are completely compatible.
Statistical Mechanics and EntropyLogarithmBayes' theoremKullback–Leibler divergenceInferencePrinciple of maximum entropyComputer scienceEntropy (arrow of time)Tsallis entropyMathematicsAlgorithm
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