MST: Minimum Spanning Tree (MST)

In DataSimilarity: Quantifying Similarity of Datasets and Multivariate Two- And k-Sample Testing

Minimum Spanning Tree (MST)

Description

Calculte the edge matrix of a minimum spanning tree based on a distance matrix, used as helper functions in CCS, CF, FR, and ZC. This function is a wrapper around mstree.

Usage

MST(dists, K = 1)

Arguments

dists	Distance matrix as dist object.
K	Component number (default: K = 1).

Details

For more details see mstree.

Value

Object of class neig.

See Also

CCS, CF, FR, ZC

Examples

set.seed(1234)
X1 <- matrix(rnorm(1000), ncol = 10)
X2 <- matrix(rnorm(1000, mean = 0.5), ncol = 10)
dists <- stats::dist(rbind(X1, X2))
if(requireNamespace("ade4", quietly = TRUE)) {
  # MST
  MST(dists)
  # 5-MST
  MST(dists, K = 5) 
}

DataSimilarity documentation built on June 16, 2025, 5:08 p.m.