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This volume has its origin in the third ·Workshop on Maximum-Entropy and Bayesian Methods in Applied Statistics,· held at the University of Wyoming, August 1 to 4, 1983. It was anticipated that the proceedings of this workshop could not be prepared in a timely fashion, so most of the papers were not collected until a year or so ago. Because most of the papers are in the nature of advancing theory or solving specific problems, as opposed to status reports, it is believed that the contents of this volume will be of lasting interest to the Bayesian community. The workshop was organized to bring together researchers from differ ent fields to examine critically maximum-entropy and Bayesian methods in science, engineering, medicine, economics, and other disciplines. Some of the papers were chosen specifically to kindle interest in new areas that may offer new tools or insight to the reader or to stimulate work on pressing problems that appear to be ideally suited to the maximum-entropy or Bayes ian method.
List of contents
Bayesian Spectrum and Chirp Analysis.- On Entropy Rate.- State Spaces and Initial Estimates in Minimum Relative-Entropy Inversion with Application to Spectrum Analysis and Image Enhancement.- Relative-Entropy Minimization with Uncertain Constraints: Theory and Application to Spectrum Analysis.- A Proof of Burg's Theorem.- A Bayesian Approach to Robust Local Facet Estimation.- The Maximum Entropy Method: The Problem of Missing Data.- On the Accuracy of Spectrum Analysis of Red Noise Processes Using Maximum Entropy and Periodogram Methods: Simulation Studies and Application to Geophysical Data.- Recent Developments at Cambridge.- Prior Knowledge must be Used.- How the Brain Works: The Next Great Scientific Revolution.- Maximum Entropy in Structural Molecular Biology: The Fiber Diffraction Phase Problem.- A Method of Computing Maximum Entropy Probability Values for Expert Systems.- Special-Purpose Algorithms for Linearly Constrained Entropy Maximization.- Bayesian Approach to Limited-Angle Reconstruction in Computed Tomography.- Application of the Maximum Entropy Principle to Retrieval from Large Data Bases.- Two Recent Applications of Maximum Entropy.- A Variational Method for Classical Fluids.- Updating Inductive Inference.- Parallel Algorithms for Maximum Entropy Calculation.
