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>.
Version: 2.0.12 Depends: R (≥ 3.2.0), bigmemory Imports: Rcpp (≥ 0.11.0), Matrix, foreach, methods LinkingTo: Rcpp, RcppEigen, BH, RSpectra (≥ 0.16-2), bigmemory, RcppArmadillo Suggests: knitr, rmarkdown Published: 2024-07-31 DOI: 10.32614/CRAN.package.oem 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.org/oem/ NeedsCompilation: yes Citation: oem citation info Materials: README CRAN checks: oem results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=oem to link to this page.
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