R: Group Lasso and Elastic Net Solver for Generalized Linear Models

# Group Lasso and Elastic Net Solver for Generalized Linear Models

## Documentation for package ‘adelie’ version 1.0.10

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

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.