The maximum entropy method and the related Bayesian probability theory have recently become better known to research workers, but the power of these methods to resolve the true structures underlying many types of data is still not widely recognized. This volume provides an account of such methods. It is designed to introduce the reader to the principles of probability theory, viewed as the logic of inference, and to explain the role that entropy plays in the assignment of probabilities. The chapters concerned with applications show how the resulting algorithms can be implemented and how they work out in practice. In addition, the text examines the relation between statistical and dynamical theories in physics, and explores the confusion which surrounds the Second Law of Thermodynamics.
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Vincent A. Macaulay is at University of Oxford.
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