gstlearn is the new cross-platform Geostatistics C++ library proposed by MINES PARIS – PSL University. It offers to users all famous Geostatistical methodologies developed and/or invented by the Geostatistic Team of the Geosciences Research Center.
gstlearn has been officially released and presented during the gstlearn workshop (2023, September 6th)
organized within the scope of the
“Journées de Géostatistiques 2023“!
minigst is a new R/Python package that wraps gstlearn with an easy-to-use API. It makes Geostatistics accessible to everyone ! It has been officially released early in December 2025. Let’s have a look to the new gstlearn’s companion here: https://github.com/gstlearn/minigst
The name ‘gstlearn‘ stands for several purposes:
– GeoSTatistics & Machine Learning Library
– Geostatistical Spatio-Temporal Learning
– Learning Geosciences & Spatio-Temporal Models
gstlearn comes in various forms:
– A C++ library (BSD)
– A Python package (BSD)
– A R package (GPL)
How to cite
When using the gstlearn C++ Library and Packages, please, use this to cite us in any publication or results for which gstlearn has been used. For example:
MINES Paris – PSL University. (2025). gstlearn/gstlearn: Release v1.9.0 (stable_1.9.0). Zenodo. https://doi.org/10.5281/zenodo.13343742
Sponsors
gstlearn is supported by the following sponsors:
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