.folds

Assigns samples to cross-validation folds,
balancing the folds in the case of a binary or survival response.

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

.folds function

<dl><dt>y</dt>
<dd>response:
vector of length \(n\)</dd>
<dt>nfolds</dt>
<dd>number of folds:
positive integer
(\(&gt;= 10\) recommended)</dd>
<dt>foldid</dt>
<dd>fold identifiers:
vector of length \(n\),
with entries from \(1\) to <code>nfolds</code></dd></dl>

Arguments

Cross-validation folds — .folds

<dl>

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


<dt>nfolds</dt>
<dd>number of folds:
positive integer
(\(&gt;= 10\) recommended)</dd>


<dt>foldid</dt>
<dd>fold identifiers:
vector of length \(n\),
with entries from \(1\) to <code>nfolds</code></dd>

</dl>

.folds: Cross-validation folds

Description

Usage

Value

Arguments

Examples