Package: adelie 1.0.3

Trevor Hastie

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

Extremely efficient procedures for fitting the entire group lasso and group elastic net regularization path for GLMs, multinomial, the Cox model and multi-task Gaussian models. Similar to the R package 'glmnet' in scope of models, and in computational speed. This package provides R bindings to the C++ code underlying the corresponding Python package 'adelie'. These bindings offer a general purpose group elastic net solver, a wide range of matrix classes that can exploit special structure to allow large-scale inputs, and an assortment of generalized linear model classes for fitting various types of data. The package includes The package is an implementation of Yang, J. and Hastie, T. (2024) <doi:10.48550/arXiv.2405.08631>.

Authors:James Yang [aut, cph], Trevor Hastie [aut, cph, cre], Balasubramanian Narasimhan [aut]

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adelie.pdf |adelie.html
adelie/json (API)
NEWS

# Install 'adelie' in R:
install.packages('adelie', repos = c('https://jamesyang007.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jamesyang007/adelie-r/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

5.43 score 3 stars 3 scripts 328 downloads 29 exports 14 dependencies

Last updated 2 months agofrom:ea37d82511. Checks:OK: 1 WARNING: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 10 2024
R-4.5-win-x86_64WARNINGOct 10 2024
R-4.5-linux-x86_64WARNINGOct 10 2024
R-4.4-win-x86_64WARNINGOct 10 2024
R-4.4-mac-x86_64WARNINGOct 10 2024
R-4.4-mac-aarch64WARNINGOct 10 2024
R-4.3-win-x86_64WARNINGOct 10 2024
R-4.3-mac-x86_64WARNINGOct 10 2024
R-4.3-mac-aarch64WARNINGOct 10 2024

Exports:coef.grpnetcv.grpnetgaussian_covglm.binomialglm.coxglm.gaussianglm.multigaussianglm.multinomialglm.poissongrpnetio.snp_phased_ancestryio.snp_unphasedmatrix.block_diagmatrix.concatenatematrix.densematrix.eager_covmatrix.interactionmatrix.kronecker_eyematrix.lazy_covmatrix.one_hotmatrix.snp_phased_ancestrymatrix.snp_unphasedmatrix.sparsematrix.standardizematrix.subsetplot.grpnetpredict.grpnetprint.cv.grpnetset_configs

Dependencies:clidigestgluelatticelifecyclemagrittrMatrixr2rRcppRcppEigenrlangstringistringrvctrs

An Introduction to adelie

Rendered fromadelie.Rmdusingknitr::rmarkdownon Oct 10 2024.

Last update: 2024-09-03
Started: 2024-06-13

Readme and manuals

Help Manual

Help pageTopics
Cross-validation for grpnetcv.grpnet
Solves group elastic net via covariance method.gaussian_cov
Creates a Binomial GLM family object.glm.binomial
Creates a Cox GLM family object.glm.cox
Creates a Gaussian GLM family object.glm.gaussian
Creates a MultiGaussian GLM family object.glm.multigaussian
Creates a Multinomial GLM family object.glm.multinomial
Creates a Poisson GLM family object.glm.poisson
fit a GLM with group lasso or group elastic-net regularizationgrpnet
IO handler for SNP phased, ancestry matrix.io.snp_phased_ancestry
IO handler for SNP unphased matrix.io.snp_unphased
Creates a block-diagonal matrix.matrix.block_diag
Creates a concatenation of the matrices.matrix.concatenate
Creates a dense matrix object.matrix.dense
Creates an eager covariance matrix.matrix.eager_cov
Creates a matrix with pairwise interactions.matrix.interaction
Creates a Kronecker product with an identity matrix.matrix.kronecker_eye
Creates a lazy covariance matrix.matrix.lazy_cov
Creates a one-hot encoded matrix.matrix.one_hot
Creates a SNP phased, ancestry matrix.matrix.snp_phased_ancestry
Creates a SNP unphased matrix.matrix.snp_unphased
Creates a sparse matrix object.matrix.sparse
Creates a standardized matrix.matrix.standardize
Creates a subset of the matrix along an axis.matrix.subset
plot the cross-validation curve produced by cv.grpnetplot.cv.grpnet
plot coefficients from a "grpnet" objectplot.grpnet
make predictions from a "cv.grpnet" object.coef.cv.grpnet predict.cv.grpnet
make predictions from a "grpnet" object.coef.grpnet predict.grpnet
print a cross-validated grpnet objectprint.cv.grpnet
print a grpnet objectprint.grpnet
Set configuration settings.set_configs