Package: smurf 1.1.5

smurf: Sparse Multi-Type Regularized Feature Modeling

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.

Authors:Tom Reynkens [aut, cre], Sander Devriendt [aut], Katrien Antonio [aut]

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smurf.pdf |smurf.html✨
smurf/json (API)
NEWS

# Install 'smurf' in R:
install.packages('smurf', repos = c('https://treynkens.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://gitlab.com/treynkens/smurf

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

13 exports 0.85 score 16 dependencies 1 dependents 26 scripts 319 downloads

Last updated 1 years agofrom:99afdc8a68. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 11 2024
R-4.5-win-x86_64OKSep 11 2024
R-4.5-linux-x86_64OKSep 11 2024
R-4.4-win-x86_64OKSep 11 2024
R-4.4-mac-x86_64OKSep 11 2024
R-4.4-mac-aarch64OKSep 11 2024
R-4.3-win-x86_64OKSep 11 2024
R-4.3-mac-x86_64OKSep 11 2024
R-4.3-mac-aarch64OKSep 11 2024

Exports:coef_reestcoefficients_reestdeviance_reestfitted_reestglmsmurfglmsmurf.controlglmsmurf.fitpplot_lambdaplot_reestpredict_reestresid_reestresiduals_reest

Dependencies:catdatacodetoolsforeachglmnetiteratorslatticeMASSMatrixmgcvnlmeRColorBrewerRcppRcppArmadilloRcppEigenshapesurvival

Introduction to the smurf package

| Tom Reynkens, Sander Devriendt and Katrien Antonio | LRisk, Faculty of Economics and Business, KU Leuven

Rendered fromsmurf.Rmdusingknitr::rmarkdownon Sep 11 2024.

Last update: 2020-09-25
Started: 2018-09-17