Running Example | L1 Fusion | L2 Fusion
Package: fuser 1.0.1
Frank Dondelinger
fuser: Fused Lasso for High-Dimensional Regression over Groups
Enables high-dimensional penalized regression across heterogeneous subgroups. Fusion penalties are used to share information about the linear parameters across subgroups. The underlying model is described in detail in Dondelinger and Mukherjee (2017) <arxiv:1611.00953>.
Authors:
fuser_1.0.1.tar.gz
fuser_1.0.1.tar.gz(r-4.7-arm64)fuser_1.0.1.tar.gz(r-4.7-x86_64)fuser_1.0.1.tar.gz(r-4.6-arm64)fuser_1.0.1.tar.gz(r-4.6-x86_64)
fuser_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fuser/json (API)
| # Install 'fuser' in R: |
| install.packages('fuser', 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 from:6cd4856235. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 196 | ||
| linux-devel-x86_64 | OK | 214 | ||
| source / vignettes | OK | 237 | ||
| linux-release-arm64 | OK | 184 | ||
| linux-release-x86_64 | OK | 247 | ||
| wasm-release | OK | 119 |
Exports:bigeigenfusedL2DescentGLMNetfusedLassoProximalfusedLassoProximalIterationsTakengenerateBlockDiagonalMatrices
Dependencies:codetoolsforeachglmnetirlbaiteratorslatticeMatrixRcppRcppEigenRSpectrashapesurvival
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Big eigenvalue calculation | bigeigen |
| Optimise the fused L2 model with glmnet (using transformed input data) | fusedL2DescentGLMNet |
| Fused lasso optimisation with proximal-gradient method. (Chen et al. 2010) | fusedLassoProximal |
| Following a call to fusedLassoProximal, returns the actual number of iterations taken. | fusedLassoProximalIterationsTaken |
| Generate block diagonal matrices to allow for fused L2 optimization with glmnet. | generateBlockDiagonalMatrices |