DEVELOPED | 2001-2005 |
AUTHOR | George Christakos and Marc Serre University of North Carolina USA Patrick Bogaert Université Catholique de Louvain Belgium marc_serre(at)unc.edu |
PLATFORM | MATLAB |
PURPOSE | Space/time geostatistics, Bayesian Maximum Entropy |
FUNCTIONS | + general statistics (histograms, probability plots) + variogram and cross variogram calculations in space/time (any spatial dimension) + BME using probabilistic and hard data + BME using interval and hard data + BME using hard data only (simple kriging) + BME using probabilistic and hard data with a trend model + BME using interval and hard data with a trend model + BME using hard data with a trend model (ordinary kriging and kriging with trend) + all estimation can use vector fields (e.g. cokriging) and be in the space/time domain + all estimation can be with transformation to handle non-Gaussian data + LU simulation + sequential gaussian simulation |
CODES | Matlab codes available on request. |
TIP | BMElib implements space/time estimation using the Bayesian Maximum Entropy (BME) theory. BME is a very general framework, which leads to the well known kriging algorithms (simple, ordinary, with mean trend model) as a special case under some limiting conditions (when unsing only hard data, etc.), but provides a more comprehensive model when using both hard AND soft data (as well as many other sorts of knowledge bases). |
HOMEPAGE | Download is available from www.unc.edu/depts/case/BMELIB/ with the permission from the authors. |