Group Lasso and Elastic Net Solver for Generalized Linear Models


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Documentation for package ‘adelie’ version 1.0.2

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coef.cv.grpnet make predictions from a "cv.grpnet" object.
coef.grpnet make predictions from a "grpnet" object.
cv.grpnet Cross-validation for grpnet
gaussian_cov Solves group elastic net via covariance method.
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.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.grpnet plot the cross-validation curve produced by cv.grpnet
plot.grpnet plot coefficients from a "grpnet" object
predict.cv.grpnet make predictions from a "cv.grpnet" object.
predict.grpnet make predictions from a "grpnet" object.
print.cv.grpnet print a cross-validated grpnet object
print.grpnet print a grpnet object
set_configs Set configuration settings.