Updating Probabilities
arXiv:physics/0608185 · doi:10.1063/1.2423258
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.
Presented at MaxEnt 2006, the 26th International Workshop on Bayesian Inference and Maximum Entropy Methods (July 8-13, 2006, Paris, France)
Cited by in corpus (8)
- Jacobi Fields on Statistical Manifolds of Negative Curvature
- Information-Geometric Indicators of Chaos in Gaussian Models on Statistical Manifolds of Negative Ricci Curvature
- Using Relative Entropy to Find Optimal Approximations: an Application to Simple Fluids
- Information Geometry and Chaos on Negatively Curved Statistical Manifolds
- Geometrodynamics of Information on Curved Statistical Manifolds and its Applications to Chaos
- Maximum Entropy: The Universal Method for Inference
- Updating Probabilities: An Econometric Example
- The relativity of theory