print.summary.cv.oem

print method for <code>summary.cv.oem</code> objects

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>.

Jared Huling

Orthogonalizing EM: Penalized Regression for Big Tall Data

Bin Dai

Yixuan Qiu

Gael Guennebaud

Jitse Niesen

print.summary.cv.oem function

<dl><dt>x</dt>
<dd>a "summary.cv.oem" object</dd>
<dt>digits</dt>
<dd>digits to display</dd>
<dt>...</dt>
<dd>not used</dd></dl>

Arguments

print method for summary.cv.oem objects — print.summary.cv.oem

<dl>

<dt>x</dt>
<dd>a "summary.cv.oem" object</dd>


<dt>digits</dt>
<dd>digits to display</dd>


<dt>...</dt>
<dd>not used</dd>

</dl>

print.summary.cv.oem: print method for `summary.cv.oem` objects

Description

Usage

Arguments