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.
| Version: |
2.0.10 |
| Depends: |
R (≥ 3.2.0), bigmemory |
| Imports: |
Rcpp (≥ 0.11.0), Matrix, foreach, methods |
| LinkingTo: |
Rcpp, RcppEigen, BH, bigmemory, RcppArmadillo |
| Suggests: |
knitr, rmarkdown |
| Published: |
2020-06-04 |
| Author: |
Bin Dai [aut],
Jared Huling 
[aut, cre],
Yixuan Qiu [ctb],
Gael Guennebaud [cph],
Jitse Niesen [cph] |
| Maintainer: |
Jared Huling <jaredhuling at gmail.com> |
| BugReports: |
https://github.com/jaredhuling/oem/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://arxiv.org/abs/1801.09661,
https://github.com/jaredhuling/oem,
https://jaredhuling.github.io/oem |
| NeedsCompilation: |
yes |
| Citation: |
oem citation info |
| Materials: |
README |
| CRAN checks: |
oem results |