| coef.cv.glintnet | make predictions from a "cv.glintnet" object. |
| coef.cv.grpnet | make predictions from a "cv.grpnet" object. |
| coef.glintnet | make predictions from a "glintnet" object. |
| coef.grpnet | make predictions from a "grpnet" object. |
| constraint.box | Create a box constraint for a group. |
| cv.glintnet | Cross-validation for glintnet |
| cv.grpnet | Cross-validation for grpnet |
| gaussian_cov | Solves group elastic net via covariance method. |
| glintnet | fit a GLM interaction model with group lasso or group elastic-net regularization |
| glm.binomial | Creates a Binomial GLM family object. |
| glm.cox | Creates a Cox GLM family object. |
| glm.gaussian | Creates a Gaussian GLM family object. |
| glm.multigaussian | Creates a MultiGaussian GLM family object. |
| glm.multinomial | Creates a Multinomial GLM family object. |
| glm.poisson | Creates a Poisson GLM family object. |
| grpnet | fit a GLM with group lasso or group elastic-net regularization |
| io.snp_phased_ancestry | IO handler for SNP phased, ancestry matrix. |
| io.snp_unphased | IO handler for SNP unphased matrix. |
| matrix.block_diag | Creates a block-diagonal matrix. |
| matrix.concatenate | Creates a concatenation of the matrices. |
| matrix.convex_relu | Creates a feature matrix for the convex relu problem. |
| matrix.dense | Creates a dense matrix object. |
| matrix.eager_cov | Creates an eager covariance matrix. |
| matrix.interaction | Creates a matrix with pairwise interactions. |
| matrix.kronecker_eye | Creates a Kronecker product with an identity matrix. |
| matrix.lazy_cov | Creates a lazy covariance matrix. |
| matrix.one_hot | Creates a one-hot encoded matrix. |
| matrix.snp_phased_ancestry | Creates a SNP phased, ancestry matrix. |
| matrix.snp_unphased | Creates a SNP unphased matrix. |
| matrix.sparse | Creates a sparse matrix object. |
| matrix.standardize | Creates a standardized matrix. |
| matrix.subset | Creates a subset of the matrix along an axis. |
| plot.cv.glintnet | plot the cross-validation curve produced by cv.glintnet |
| plot.cv.grpnet | plot the cross-validation curve produced by cv.glintnet |
| plot.grpnet | plot coefficients from a "grpnet" object |
| predict.cv.glintnet | make predictions from a "cv.glintnet" object. |
| predict.cv.grpnet | make predictions from a "cv.grpnet" object. |
| predict.glintnet | make predictions from a "glintnet" object. |
| predict.grpnet | make predictions from a "grpnet" object. |
| print.cv.grpnet | print a cross-validated grpnet object |
| print.glintnet | Print a summary of the glintnet path at each step along the path. |
| print.grpnet | print a grpnet object |
| set_configs | Set configuration settings. |