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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

.weight function

<dl><dt>cor</dt>
<dd>correlation coefficients:
list of \(k\) vectors of length \(p\)
(one vector for each covariate set with
one entry for each covariate)</dd>
<dt>args</dt>
<dd>options for paired lasso:
list of arguments
(output from .dims and .args)</dd></dl>

Arguments

Weighting schemes — .weight

<dl>

<dt>cor</dt>
<dd>correlation coefficients:
list of \(k\) vectors of length \(p\)
(one vector for each covariate set with
one entry for each covariate)</dd>


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

</dl>

.weight: Weighting schemes

Description

Usage

Value

Arguments

Examples