Package: ADMM 0.3.3
Kisung You
ADMM: Algorithms using Alternating Direction Method of Multipliers
Provides algorithms to solve popular optimization problems in statistics such as regression or denoising based on Alternating Direction Method of Multipliers (ADMM). See Boyd et al (2010) <doi:10.1561/2200000016> for complete introduction to the method.
Authors:
ADMM_0.3.3.tar.gz
ADMM_0.3.3.tar.gz(r-4.5-noble)ADMM_0.3.3.tar.gz(r-4.4-noble)
ADMM_0.3.3.tgz(r-4.4-emscripten)ADMM_0.3.3.tgz(r-4.3-emscripten)
ADMM.pdf |ADMM.html✨
ADMM/json (API)
NEWS
| # Install 'ADMM' in R: |
| install.packages('ADMM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:ba22cd80db. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 05 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 05 2024 |
Exports:admm.bpadmm.enetadmm.genlassoadmm.ladadmm.lassoadmm.rpcaadmm.sdpadmm.spcaadmm.tv
Dependencies:codetoolsdoParallelforeachiteratorslatticeMatrixrbibutilsRcppRcppArmadilloRdpack
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| ADMM : Algorithms using Alternating Direction Method of Multipliers | ADMM-package ADMM |
| Basis Pursuit | admm.bp |
| Elastic Net Regularization | admm.enet |
| Generalized LASSO | admm.genlasso |
| Least Absolute Deviations | admm.lad |
| Least Absolute Shrinkage and Selection Operator | admm.lasso |
| Robust Principal Component Analysis | admm.rpca |
| Semidefinite Programming | admm.sdp |
| Sparse PCA | admm.spca |
| Total Variation Minimization | admm.tv |
