Package: grpnet 0.6
Nathaniel E. Helwig
grpnet: Group Elastic Net Regularized GLMs and GAMs
Efficient algorithms for fitting generalized linear and additive models with group elastic net penalties as described in Helwig (2024) <doi:10.1080/10618600.2024.2362232>. Implements group LASSO, group MCP, and group SCAD with an optional group ridge penalty. Computes the regularization path for linear regression (gaussian), logistic regression (binomial), multinomial logistic regression (multinomial), log-linear count regression (poisson and negative.binomial), and log-linear continuous regression (gamma and inverse gaussian). Supports default and formula methods for model specification, k-fold cross-validation for tuning the regularization parameters, and nonparametric regression via tensor product reproducing kernel (smoothing spline) basis function expansion.
Authors:
grpnet_0.6.tar.gz
grpnet_0.6.tar.gz(r-4.5-noble)grpnet_0.6.tar.gz(r-4.4-noble)
grpnet_0.6.tgz(r-4.4-emscripten)grpnet_0.6.tgz(r-4.3-emscripten)
grpnet.pdf |grpnet.html✨
grpnet/json (API)
| # Install 'grpnet' in R: |
| install.packages('grpnet', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- auto - Auto MPG Data Set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:65dd82783f. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 11 2024 |
| R-4.5-linux-x86_64 | OK | Dec 11 2024 |
Exports:coef.cv.grpnetcoef.grpnetcv.comparecv.grpnetcv.grpnet.defaultcv.grpnet.formulafamily.grpnetgrpnetgrpnet.defaultgrpnet.formulaplot.cv.grpnetplot.grpnetpredict.cv.grpnetpredict.grpnetprint.coef.grpnetprint.cv.grpnetprint.grpnetR_grpnet_binomialR_grpnet_gammaR_grpnet_gaussianR_grpnet_invgausR_grpnet_maxeigvalR_grpnet_multinomR_grpnet_negbinR_grpnet_penaltyrkrk.model.matrixrow.kroneckervisualize.penaltyvisualize.shrink
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Auto MPG Data Set | auto |
| Extract Coefficients for cv.grpnet and grpnet Fits | coef.cv.grpnet coef.grpnet |
| Compare Multiple cv.grpnet Solutions | cv.compare |
| Cross-Validation for grpnet | cv.grpnet cv.grpnet.default cv.grpnet.formula |
| Prepare 'family' Argument for grpnet | family.grpnet |
| Fit a Group Elastic Net Regularized GLM/GAM | grpnet grpnet.default grpnet.formula |
| Plot Cross-Validation Curve for cv.grpnet Fits | plot.cv.grpnet |
| Plot Regularization Path for grpnet Fits | plot.grpnet |
| Predict Method for cv.grpnet Fits | predict.cv.grpnet |
| Predict Method for grpnet Fits | predict.grpnet |
| S3 'print' Methods for grpnet | print.coef.grpnet print.cv.grpnet print.grpnet |
| Reproducing Kernel Basis | rk |
| Construct Design Matrices via Reproducing Kernels | rk.model.matrix |
| Row-Wise Kronecker Product | row.kronecker |
| Startup Message for grpnet | grpnetStartupMessage StartupMessage |
| Plots grpnet Penalty Function or its Derivative | visualize.penalty |
| Plots grpnet Shrinkage Operator or its Estimator | visualize.shrink |