SWBMELib < AI_GEOSTATS

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---++ BMElib 2.0

Below is the detail information:

| DEVELOPED | 2001-2005 |
| AUTHOR | George Christakos and Marc Serre <br />University of North Carolina <br />USA<br /><br />Patrick Bogaert <br />Université Catholique de Louvain <br />Belgium<br /><br />[[mailto:marc_serre@unc.edu][marc_serre(at)unc.edu]] |
| PLATFORM | MATLAB |
| PURPOSE | Space/time geostatistics, Bayesian Maximum Entropy |
| FUNCTIONS | + general statistics (histograms, probability plots) <br />+ variogram and cross variogram calculations in space/time (any spatial dimension) <br /><br />+ BME using probabilistic and hard data <br />+ BME using interval and hard data <br />+ BME using hard data only (simple kriging) <br />+ BME using probabilistic and hard data with a trend model <br />+ BME using interval and hard data with a trend model <br />+ BME using hard data with a trend model (ordinary kriging and kriging with trend) <br />+ all estimation can use vector fields (e.g. cokriging) and be in the space/time domain <br />+ all estimation can be with transformation to handle non-Gaussian data <br />+ LU simulation <br />+ 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 <a target="_blank" href="http://www.unc.edu/depts/case/BMELIB/">www.unc.edu/depts/case/BMELIB/</a> with the permission from the authors. |

Topic revision: r3 - 2010-08-18 - 19:32:48 - TheresiaFreska

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