rank_mats

This function computes the rank matrix based on the specified graph type and
number of neighbors.

Implements the Multi-view Aggregated Two-Sample (MATES) test, a powerful nonparametric method for testing equality of two multivariate distributions. The method constructs multiple graph-based statistics from various perspectives (views) including different distance metrics, graph types (nearest neighbor graphs, minimum spanning trees, and robust nearest neighbor graphs), and weighting schemes. These statistics are then aggregated through a quadratic form to achieve improved statistical power. The package provides both asymptotic closed-form inference and permutation-based testing procedures. For methodological details, see Cai and others (2026+) <doi:10.48550/arXiv.2412.16684>.

Zexi Cai

MATES

Multi-View Aggregated Two Sample Tests

Mingshuo Liu

Wenbo Fei

Doudou Zhou

rank_mats function

<dl><dt>S</dt>
<dd>A numeric matrix representing the similarity matrix</dd>
<dt>Dd</dt>
<dd>A dist object representing the distance matrix</dd>
<dt>gtype</dt>
<dd>A character string indicating the graph type to use
("NNG", "MST", or "rNNG")</dd>
<dt>k</dt>
<dd>A numeric representing the number of neighbors to use for graph</dd></dl>

Arguments

Compute rank matrix — rank_mats

<dl>

<dt>S</dt>
<dd>A numeric matrix representing the similarity matrix</dd>


<dt>Dd</dt>
<dd>A dist object representing the distance matrix</dd>


<dt>gtype</dt>
<dd>A character string indicating the graph type to use
("NNG", "MST", or "rNNG")</dd>


<dt>k</dt>
<dd>A numeric representing the number of neighbors to use for graph</dd>

</dl>

rank_mats: Compute rank matrix

Description

Usage

Value

Arguments

References