search_tree: Search Tree Function

In tpq/propr: An R package to calculate proportionality and other measures for compositional data

Search Tree Function

Description

This function performs a hierarchical clustering on the given data and identifies the best clusters based on variance explained by Canonical Correspondence Analysis (CCA).

Usage

search_tree(data, Z, nclust = ncol(data)/10, nsearch = 1, lrm = NULL)

Arguments

data	The input data matrix for clustering.
Z	The matrix used to fit vegan model.
nclust	The number of clusters to create during hierarchical clustering. Default is calculated as ncol(data) / 10.
nsearch	The number of best clusters to search for. Default is 1.
lrm	The Log Ratio Matrix. Default is NULL.

Value

A numeric vector containing the percentage of variance explained by CCA for each cluster identified.

tpq/propr documentation built on April 21, 2024, 12:50 p.m.