.fit

Fits all models from the chosen bag.

internal

Implements sparse regression with paired covariates (<doi:10.1007/s11634-019-00375-6>). The paired lasso is designed for settings where each covariate in one set forms a pair with a covariate in the other set (one-to-one correspondence). For the optional correlation shrinkage, install ashr (<https://github.com/stephens999/ashr>) and CorShrink (<https://github.com/kkdey/CorShrink>) from GitHub (see README).

Armin Rauschenberger

palasso

Sparse Regression with Paired Covariates

.fit function

<dl><dt>y</dt>
<dd>response:
vector of length \(n\)</dd>
<dt>x</dt>
<dd>covariates:
matrix with \(n\) rows (samples)
and \(k * p\) columns (variables)</dd>
<dt>args</dt>
<dd>options for paired lasso:
list of arguments
(output from .dims and .args)</dd></dl>

Arguments

Model bag — .fit

<dl>

<dt>y</dt>
<dd>response:
vector of length \(n\)</dd>


<dt>x</dt>
<dd>covariates:
matrix with \(n\) rows (samples)
and \(k * p\) columns (variables)</dd>


<dt>args</dt>
<dd>options for paired lasso:
list of arguments
(output from .dims and .args)</dd>

</dl>

.fit: Model bag

Description

Usage

Value

Arguments

Examples