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oem
View on CRAN: Click
here
Download and install oem package within the R console
Install from CRAN:
install.packages("oem")
Install from Github:
library("remotes")
install_github("cran/oem")
Install by package version:
library("remotes")
install_version("oem", "2.0.11")
Attach the package and use:
library("oem")
Maintained by
Jared Huling
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-09-09
Latest Update: 2022-10-13
Description:
Solves penalized least squares problems for big tall data
using the orthogonalizing EM algorithm of Xiong et al. (2016)
. 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) .
How to cite:
Jared Huling (2012). oem: Orthogonalizing EM: Penalized Regression for Big Tall Data. R package version 2.0.11, https://cran.r-project.org/web/packages/oem
Previous versions and publish date:
1.01 (2012-09-09 19:10), 1.02.1 (2014-01-06 17:30), 1.02 (2012-12-30 08:12), 2.0.1 (2016-10-19 12:58), 2.0.2 (2016-10-25 20:32), 2.0.3 (2016-10-26 10:37), 2.0.4 (2017-02-21 08:43), 2.0.5 (2017-03-22 13:16), 2.0.6 (2017-07-06 16:41), 2.0.7 (2018-02-01 06:21), 2.0.8 (2018-03-26 06:05), 2.0.9 (2018-10-30 11:40), 2.0.10 (2020-06-04 14:00)
Other packages that cited oem R package
View oem citation profile
Other R packages that oem depends,
imports, suggests or enhances
Functions, R codes and Examples using
the oem R package
Some associated functions: big.oem . cv.oem . deprecated . logLik . oem . oem.xtx . plot . predict.cv.oem . predict.oem . predict.xval.oem . print . summary . xval.oem .
Some associated R codes: big_oem.R . cv_oem.R . deprecated_functions.R . methods.R . oem.R . oem_xtx.R . oem_xval.R . utils.R . Full oem package functions and examples
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