Difference: SWBMELib (2 vs. 3)

Revision 32010-08-18 - TheresiaFreska

 
META TOPICPARENT name="SoftwareCodes"

BMElib 2.0

Below is the detail information:

DEVELOPED 2001-2005
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AUTHOR George Christakos and Marc Serre
University of North Carolina
USA

Patrick Bogaert
Universit? Catholique de Louvain
Belgium

marc_serre@unc.edu
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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
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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
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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.
 
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