rlang, magrittr, dplyr, stringr, purrr, curl, jsonlite, readr

Fit penalized regression with orthogonalizing EM algorithm

c(
person("Bin", "Dai", , "bdai@uwalumni.com", role = c("aut")),
person("Jared", "Huling", , "jaredhuling@gmail.com", c("aut", "cre")),
person("Yixuan", "Qiu", , , c("ctb"))
)
Solves penalized least squares problems 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.
Rcpp (>= 0.11.0), Matrix, foreach, methods
Rcpp, RcppEigen, BH, bigmemory, RcppArmadillo
Bin Dai [aut],
Jared Huling [aut, cre],
Yixuan Qiu [ctb]

Orthogonalizing EM: Penalized Regression for Big Tall Data
c(
person("Bin", "Dai", , "bdai@uwalumni.com", role = c("aut")),
person("Jared", "Huling", , "jaredhuling@gmail.com", c("aut", "cre"),
comment = c(ORCID = "0000-0003-0670-4845")),
person("Yixuan", "Qiu", , , c("ctb")),
person("Gael", "Guennebaud", , , c("cph")),
person("Jitse", "Niesen", , , c("cph"))
)
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.
Bin Dai [aut],
Jared Huling [aut, cre] (<https://orcid.org/0000-0003-0670-4845>),
Yixuan Qiu [ctb],
Gael Guennebaud [cph],
Jitse Niesen [cph]

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>.