Package: smurf 1.1.8

Tom Reynkens
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:
smurf_1.1.8.tar.gz
smurf_1.1.8.tar.gz(r-4.7-arm64)smurf_1.1.8.tar.gz(r-4.7-x86_64)smurf_1.1.8.tar.gz(r-4.6-arm64)smurf_1.1.8.tar.gz(r-4.6-x86_64)
smurf_1.1.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
smurf/json (API)
| # Install 'smurf' in R: |
| install.packages('smurf', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://gitlab.com/treynkens/smurf
Last updated from:03e1bf021b. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 206 | ||
| linux-devel-x86_64 | OK | 212 | ||
| source / vignettes | OK | 223 | ||
| linux-release-arm64 | OK | 200 | ||
| linux-release-x86_64 | OK | 209 | ||
| wasm-release | OK | 621 |
Exports:coef_reestcoefficients_reestdeviance_reestfitted_reestglmsmurfglmsmurf.controlglmsmurf.fitpplot_lambdaplot_reestpredict_reestresid_reestresiduals_reest
Dependencies:catdatacodetoolsforeachglmnetiteratorslatticeMASSMatrixmgcvnlmeRColorBrewerRcppRcppArmadilloRcppEigenshapesurvival