BMElib is a powerful MATLAB numerical toolbox of Modern Spatiotemporal Geostatistics implementing the Bayesian Maximum Entropy (BME) theory. It can be used for any of the following:
- both spatial and space/time Geostatistics, dealing with
- both continuous and categorical variables, implementing
- the best unbiased non linear estimator (BME), which
- rigorously processes hard and soft data, but also leads to
- the (simple, ordinary, universal) kriging methods as linear limiting cases.
Unlike other Geostatistical package, BMElib has been implemented from the start for space/time Geostatistics. Hence BMElib implements the concepts of space/time metrics, space/time neighborhood search, space/time covariance analysis, and space/time estimation. As a result BMElib provides better Geostatistical functions for space/time analysis than classical Geostatistics software (where time is included as merely another spatial dimension), while providing excellent functions in the purely spatial case.
BMElib implements the powerful BME method of Modern Spatiotemporal Geostatistics. BME is a rigorous mathematical framework that allows processing a wide variety of knowledge bases, and leads to the best unbiased non linear estimator. Hard data, soft data, non-Gaussian distributions, etc are automatically integrated in BMElib.
When restricting the estimation to linear estimation of continuous variables, BME becomes the best unbiased linear estimators of classical Geostatistics. Hence simple kriging, ordinary kriging, universal kriging, etc. are all part of the BMElib toolbox.
BMElib is a publicly available software for BMElib users. To get on the BMElib users list, send an email to marc_serre@unc.edu (USA contact) or patrick.bogaert@uclouvain.be (European contact) or with your contact information (name, position, work address) stating your interest to be added to the list.