This organization is dedicated to libKriging project: a C++ library for Kriging/Gaussian process regression.
Main features of libKriging are:
- Standard implementation of most common kriging:
- ordinary/universal kriging
- nugget (homoskedastic) or noise (heteroskedastic)
- optimization of hyper-parameters (range, nugget, variance, ...) based on log-likelihood, leave-one-out, log-marginal-posterior
- (pre-)normalization of conditional data
- Comparison/testing against some standarad kriging libraries:
- Compatibility with commons OS:
- Windows
- Linux
- OSX (intel & ARM)
- (Almost) full wrapper availables for:
- Python: https://pypi.org/project/pylibkriging/
- R: https://github.com/libKriging/rlibkriging
- Octave
- Matlab
- Documentation: https://libKriging.readthedocs.io
Entry points:
- for users: https://libKriging.readthedocs.io
- for developpers: https://github.com/libKriging/libkriging