Bayesian Inference and Maximum Entropy Methods in Science and Engineering: Proceedings of the 28th International Workshop
Marcelo de Souza Lauretto, Carlos A. de Braganša Pereira, Julio Michael Stern
American Inst. of Physics, Dec 4, 2008 - Computers - 394 pages
The MaxEnt2008 - 28th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering - encompassed all aspects of information theory, probability, statistical inference and statistical physics, including research on foundations and theoretical developments, as well as modeling techniques for several specific application areas.
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2008 American Institute algorithm analysis application approach approximation assume Bayes Bayesian Inference Braganca Pereira C. A. de Braganca calculated Caticha chiral chiral index coefficients cointegration components compute consider constraints curves defined dependence derived dimension downset elements energy entropic dynamics entropy of mixing equation estimation example exponential expression factor FBST Figure finite Gaussian Gibbs paradox given hazard function Inference and Maximum Information Geometry information theory Institute of Physics International Workshop edited J. M. Stem lag length lattice likelihood function linear Markov mathematical matrix maximizing Maximum Entropy Methods maximum likelihood ME-Burg measure Methods in Science microstates mixture observed obtained optimal parameter poset posterior distribution prior distribution probability density probability distribution problem proposed quantum queues random variable regression relation robot sample simulated Souza Lauretto spatial statistical manifolds structure symmetry Theorem variance variational Bayes vector Weibull Weibull distribution