log_wilks_lambda

Calculates the log of Wilks' lambda statistic
for a given <code>super_sample</code> object.
This function ensures that the within-group
and total covariance matrices are computed,
then computes the difference of their log determinants.

Provides statistical methods for analyzing samples of symmetric
positive definite (SPD) matrices, particularly functional connectivity
matrices from neuroimaging data. Implements Fréchet ANOVA
(Dubey and Müller (2019) <doi:10.1093/biomet/asz052>) for testing
differences between groups in metric spaces, and Riemannian ANOVA methods
that leverage tangent space geometry with classic multivariate test
statistics including Wilks' Lambda and Pillai's trace. Also includes
harmonization techniques for removing batch effects in multi-site studies:
ComBat-based harmonization (Honnorat et al. (2024)
<doi:10.1016/j.media.2023.103043>) and rigid harmonization
(Simeon et al. (2022) <doi:10.3389/fninf.2022.769274>). Builds on
'riemtan' package infrastructure for efficient computation with multiple
Riemannian metrics.

Nicolas Escobar

riemstats

Riemannian ANOVA Statistics

Jaroslaw Harezlak

log_wilks_lambda function

<dl><dt>super_sample</dt>
<dd>An object of class CSuperSample</dd></dl>

Arguments

Compute the Log Wilks' Lambda Statistic — log_wilks_lambda

<dl>

<dt>super_sample</dt>
<dd>An object of class CSuperSample</dd>

</dl>

log_wilks_lambda: Compute the Log Wilks' Lambda Statistic

Description

Usage

Value

Arguments

Details