.stationary_bootstrap

Implements the stationary bootstrap of Politis &amp; Romano (1994),
which resamples contiguous blocks of variable length to preserve
weak temporal dependence while maintaining ergodicity.

internal

Prevents and detects information leakage in biomedical machine learning.
Provides leakage-resistant split policies (subject-grouped, batch-blocked, study leave-out, time-ordered),
guarded preprocessing (train-only imputation, normalization, filtering, feature selection),
cross-validated fitting with common learners, permutation-gap auditing, batch and fold association tests,
and duplicate detection.

Selcuk Korkmaz

bioLeak

Leakage-Safe Modeling and Auditing for Genomic and Clinical Data

.stationary_bootstrap function

<dl><dt>idx</dt>
<dd>Integer vector of ordered indices.</dd>
<dt>mean_block</dt>
<dd>Positive numeric, expected block length.</dd></dl>

Arguments

Stationary bootstrap indices — .stationary_bootstrap

<dl>

<dt>idx</dt>
<dd>Integer vector of ordered indices.</dd>


<dt>mean_block</dt>
<dd>Positive numeric, expected block length.</dd>

</dl>

.stationary_bootstrap: Stationary bootstrap indices

Description

Usage

Value

Arguments

References