print.abess

Prints the fitted model and returns it invisibly.

Extremely efficient toolkit for solving the best subset selection problem <https://www.jmlr.org/papers/v23/21-1060.html>. This package is its R interface. The package implements and generalizes algorithms designed in <doi:10.1073/pnas.2014241117> that exploits a novel sequencing-and-splicing technique to guarantee exact support recovery and globally optimal solution in polynomial times for linear model. It also supports best subset selection for logistic regression, Poisson regression, Cox proportional hazard model, Gamma regression, multiple-response regression, multinomial logistic regression, ordinal regression, (sequential) principal component analysis, and robust principal component analysis. The other valuable features such as the best subset of group selection <doi:10.1287/ijoc.2022.1241> and sure independence screening <doi:10.1111/j.1467-9868.2008.00674.x> are also provided.

Jin Zhu

abess

Fast Best Subset Selection

Zezhi Wang

Liyuan Hu

Junhao Huang

Kangkang Jiang

Yanhang Zhang

Borui Tang

Shiyun Lin

Junxian Zhu

Canhong Wen

Heping Zhang

Xueqin Wang

spectra contributors 

print.abess function

<dl><dt>x</dt>
<dd>A "<code>abess</code>" object.</dd>
<dt>digits</dt>
<dd>Minimum number of significant digits to be used.</dd>
<dt>...</dt>
<dd>additional print arguments</dd></dl>

Arguments

Print method for a fitted "abess" object — print.abess

<dl>

<dt>x</dt>
<dd>A "<code>abess</code>" object.</dd>


<dt>digits</dt>
<dd>Minimum number of significant digits to be used.</dd>


<dt>...</dt>
<dd>additional print arguments</dd>

</dl>

Print method for a fitted "<code>abess</code>" object

print.abess: Print method for a fitted "`abess`" object

Description

Usage

Value

Arguments

Details

See Also