On Shannon-Jaynes Entropy and Fisher Information
Data Analysis, Statistics and Probability
2009-11-13 v1 General Physics
Abstract
The fundamentals of the Maximum Entropy principle as a rule for assigning and updating probabilities are revisited. The Shannon-Jaynes relative entropy is vindicated as the optimal criterion for use with an updating rule. A constructive rule is justified which assigns the probabilities least sensitive to coarse-graining. The implications of these developments for interpreting physics laws as rules of inference upon incomplete information are briefly discussed.
Keywords
Cite
@article{arxiv.0708.2879,
title = {On Shannon-Jaynes Entropy and Fisher Information},
author = {Vesselin I. Dimitrov},
journal= {arXiv preprint arXiv:0708.2879},
year = {2009}
}
Comments
Presented at the 27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Saratoga Springs, NY, July 8-13, 2007