Package: oem 2.0.12

Jared Huling

oem: Orthogonalizing EM: Penalized Regression for Big Tall Data

Solves penalized least squares problems for big tall data using the orthogonalizing EM algorithm of Xiong et al. (2016) <doi:10.1080/00401706.2015.1054436>. The main fitting function is oem() and the functions cv.oem() and xval.oem() are for cross validation, the latter being an accelerated cross validation function for linear models. The big.oem() function allows for out of memory fitting. A description of the underlying methods and code interface is described in Huling and Chien (2022) <doi:10.18637/jss.v104.i06>.

Authors:Bin Dai [aut], Jared Huling [aut, cre], Yixuan Qiu [ctb], Gael Guennebaud [cph], Jitse Niesen [cph]

oem_2.0.12.tar.gz
oem_2.0.12.tar.gz(r-4.7-arm64)oem_2.0.12.tar.gz(r-4.7-x86_64)oem_2.0.12.tar.gz(r-4.6-arm64)oem_2.0.12.tar.gz(r-4.6-x86_64)
oem_2.0.12.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
oem/json (API)

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

Bug tracker:https://github.com/jaredhuling/oem/issues

Pkgdown/docs site:https://jaredhuling.org

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

On CRAN:

Conda:

openblascppopenmp

3.61 score 1 packages 27 scripts 288 downloads 1 mentions 7 exports 13 dependencies

Last updated from:98789746bc. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK329
linux-devel-x86_64OK269
source / vignettesOK454
linux-release-arm64OK257
linux-release-x86_64OK279
wasm-releaseOK197

Exports:big.oemcv.oemcv.oemfitoemoem.xtxoemfitxval.oem

Dependencies:BHbigmemorybigmemory.sricodetoolsforeachiteratorslatticeMatrixRcppRcppArmadilloRcppEigenRSpectrauuid

Usage of the oem Package

Jared Huling

Rendered fromoem_vignette.Rmdusingknitr::rmarkdownon Jun 13 2026.

Last update: 2022-10-13
Started: 2016-10-19