Package: sparseLTSEigen 0.2.1

sparseLTSEigen: RcppEigen back end for sparse least trimmed squares regression

Use RcppEigen to fit least trimmed squares regression models with an L1 penalty in order to obtain sparse models.

Authors:Andreas Alfons [aut, cre]

sparseLTSEigen_0.2.1.tar.gz
sparseLTSEigen_0.2.1.zip(r-4.7-x86_64)sparseLTSEigen_0.2.1.zip(r-4.7-arm64)sparseLTSEigen_0.2.1.zip(r-4.6-x86_64)sparseLTSEigen_0.2.1.zip(r-4.6-arm64)sparseLTSEigen_0.2.1.zip(r-4.5-x86_64)
sparseLTSEigen_0.2.1.tgz(r-4.6-x86_64)sparseLTSEigen_0.2.1.tgz(r-4.6-arm64)sparseLTSEigen_0.2.1.tgz(r-4.5-x86_64)sparseLTSEigen_0.2.1.tgz(r-4.5-arm64)
sparseLTSEigen_0.2.1.tar.gz(r-4.7-arm64)sparseLTSEigen_0.2.1.tar.gz(r-4.7-x86_64)sparseLTSEigen_0.2.1.tar.gz(r-4.6-arm64)sparseLTSEigen_0.2.1.tar.gz(r-4.6-x86_64)
sparseLTSEigen_0.2.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
sparseLTSEigen/json (API)

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

Bug tracker:https://github.com/aalfons/sparseltseigen/issues

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

On CRAN:

Conda:

cppopenmp

2.00 score 1 stars 1 scripts 261 downloads 1 exports 25 dependencies

Last updated from:ec86d44a7d. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK151
linux-devel-x86_64OK121
source / vignettesOK164
linux-release-arm64OK138
linux-release-x86_64OK153
macos-release-arm64OK141
macos-release-x86_64OK214
macos-oldrel-arm64OK136
macos-oldrel-x86_64OK447
windows-devel-arm64OK203
windows-devel-x86_64OK185
windows-release-arm64OK312
windows-release-x86_64OK117
windows-oldrel-x86_64OK133
wasm-releaseOK124

Exports:.CallSparseLTSEigen

Dependencies:clicpp11DEoptimRfarverggplot2gluegtableisobandlabelinglifecycleMASSperryR6RColorBrewerRcppRcppArmadilloRcppEigenrlangrobustbaserobustHDS7scalesvctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
RcppEigen back end for sparse least trimmed squares regressionsparseLTSEigen-package .CallSparseLTSEigen sparseLTSEigen