coef.abessrpca

This function provides estimated
coefficients from a fitted "<code>abessrpca</code>" object.

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 

coef.abessrpca function

<dl><dt>object</dt>
<dd>An "<code>abessrpca</code>" project.</dd>
<dt>support.size</dt>
<dd>An integer vector specifies
the sparse matrix fitted at given <code>support.size</code> to be returned.
If <code>support.size = NULL</code>, then the sparse matrix with 
the least tuning value would be returned.
Default: <code>support.size = NULL</code>.</dd>
<dt>sparse</dt>
<dd>A logical value, specifying whether the coefficients should be
presented as sparse matrix or not. Default: <code>sparse = TRUE</code>.</dd>
<dt>...</dt>
<dd>Other arguments.</dd></dl>

Arguments

Extract sparse component from a fitted "abessrpca" object. — coef.abessrpca

<dl>

<dt>object</dt>
<dd>An "<code>abessrpca</code>" project.</dd>


<dt>support.size</dt>
<dd>An integer vector specifies
the sparse matrix fitted at given <code>support.size</code> to be returned.
If <code>support.size = NULL</code>, then the sparse matrix with 
the least tuning value would be returned.
Default: <code>support.size = NULL</code>.</dd>


<dt>sparse</dt>
<dd>A logical value, specifying whether the coefficients should be
presented as sparse matrix or not. Default: <code>sparse = TRUE</code>.</dd>


<dt>...</dt>
<dd>Other arguments.</dd>

</dl>

Extract sparse component from a fitted "<code>abessrpca</code>" object.

coef.abessrpca: Extract sparse component from a fitted "`abessrpca`" object.

Description

Usage

Value

Arguments