The present paper reviews the conceptual framework and development of the Bayesian
Maximum Entropy (BME) approach. BME has been considered as a significant breakthrough …

Due to the fast pace increasing availability and diversity of information sources in
environmental sciences, there is a real need of sound statistical mapping techniques for …

This paper is concerned with a computational formulation of the Bayesian maximum entropy
(BME) mapping method, which can handle rigorously and efficiently spatiotemporal …

Abstract Bayesian Maximum Entropy (BME) has been successfully used in geostatistics to
calculate predictions of spatial variables given some general knowledge base and sets of …

Abstract The Bayesian Maximum Entropy (BME) method of spatial analysis and mapping
provides definite rules for incorporating prior information, hard and soft data into the …

During the past decade, the Bayesian maximum entropy (BME) approach has been used
with considerable success in a variety of geostatistical applications, including the …

This volume has its origin in the Fifth, Sixth and Seventh Workshops on" Maximum-Entropy
and Bayesian Methods in Applied Statistics", held at the University of Wyoming, August 5-8 …

Maximum Entropy and Bayesian Methods: Santa Fe, New Mexico, USA, 1995 Proceedings of
the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods Page 1 …

This is the second edition of the first tutorial book on Bayesian methods and maximum
entropy aimed at senior undergraduates in science and engineering. It takes the mystery out …

Maps of temporal and spatial values of annual averages of daily particulate matter (PM10)
concentrations were generated throughout the state of California using uncertain forms of …