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Efficient implementations for Sorted L-One Penalized Estimation (SLOPE):generalized linear models regularized with the sorted L1-norm. There issupport for ordinary least-squares regression, binomial regression,multinomial regression, and poisson regression, as well as both denseand sparse predictor matrices. In addition, the package featurespredictor screening rules that enable efficient solutions tohigh-dimensional problems.

You can install the current stable release fromCRAN with

install.packages("SLOPE")

or the development version fromGitHub with

# install.packages("remotes")remotes::install_github("jolars/SLOPE")

SLOPE usessemantic versioning.

Please note that the ‘SLOPE’ project is released with aContributorCode of Conduct.By contributing to this project, you agree to abide by its terms.