The sprm
package has been sunset and will no longer be updated.
Its contents have migrated into the direpack
package:
The sprm
package in this final version will still stay live for a while for backwards compatibility.
The package is distributed through PyPI, so install through:
pip install sprm
Detailed documentation on how to use the classes is provided in the Documentation file.
For examples, please have a look at the SPRM Examples Notebook.
- Sparse partial robust M regression, Irene Hoffmann, Sven Serneels, Peter Filzmoser, Christophe Croux, Chemometrics and Intelligent Laboratory Systems, 149 (2015), 50-59.
- Partial robust M regression, Sven Serneels, Christophe Croux, Peter Filzmoser, Pierre J. Van Espen, Chemometrics and Intelligent Laboratory Systems, 79 (2005), 55-64.
- Sparse and robust PLS for binary classification, I. Hoffmann, P. Filzmoser, S. Serneels, K. Varmuza, Journal of Chemometrics, 30 (2016), 153-162.
Release Notes can be checked out in the repository.