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Bayesian Shannon entropy estimation under normalized inverse Gaussian priors via Monte Carlo sampling
Last modified: 2023-07-02
Abstract
An analytical solution to Bayesian Shannon entropy estimation under
general Gibbs-type priors has been devised in 2014 as a limiting case of Bayesian Tsallis entropy estimation. Here we propose a different approach and derive a Monte Carlo solution under normalized Inverse Gaussian prior relying on known results for its stick-breaking representation.
general Gibbs-type priors has been devised in 2014 as a limiting case of Bayesian Tsallis entropy estimation. Here we propose a different approach and derive a Monte Carlo solution under normalized Inverse Gaussian prior relying on known results for its stick-breaking representation.