ssmurf-package: ssmurf: Sparse Multi-Type Regularized Feature Modeling...
In BavoDC/ssmurf: Sparse Multi-Type Regularized Feature Modeling (package for testing purposes)
Description
Author(s)
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Description
Adjusted version of the original smurf package. Hopefully the extra s in ssmurf stands for speedy and not slow. The original package is an implementation of the SMuRF algorithm of Devriendt et al. (2021) <doi:10.1016/j.insmatheco.2020.11.010> to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood.
Author(s)
Maintainer: Tom Reynkens tomreynkens@hotmail.com (ORCID)
Authors:
Bavo DC Campo bavo.decock@kuleuven.be
Sander Devriendt sander.devriendt@kuleuven.be
Katrien Antonio
See Also
Useful links:
BavoDC/ssmurf documentation built on Dec. 17, 2021, 10:46 a.m.
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Description Author(s) See Also
Description
Adjusted version of the original smurf package. Hopefully the extra s in ssmurf stands for speedy and not slow. The original package is an implementation of the SMuRF algorithm of Devriendt et al. (2021) <doi:10.1016/j.insmatheco.2020.11.010> to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood.
Author(s)
Maintainer: Tom Reynkens tomreynkens@hotmail.com (ORCID)
Authors:
Bavo DC Campo bavo.decock@kuleuven.be
Sander Devriendt sander.devriendt@kuleuven.be
Katrien Antonio
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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