compute.stats: Tree Dimension Test Related Statistics

In TreeDimensionTest: Trajectory Presence and Heterogeneity in Multivariate Data

Tree Dimension Test Related Statistics

Description

Computes tree dimension measure, tree dimension test effect, number leafs and tree diameter from MST of a given dataset

Usage

compute.stats(x, MST = c("boruvka", "exact"), dim.reduction = c("pca", "none"))

Arguments

x	matrix of input data. Rows as observations and columns as features
MST	name of MST to be used in test. There are 2 options; "exact" MST and "boruvka" which is faster for large samples
dim.reduction	string parameter with value "pca" to perform dimensionality reduction or "none" to not perform dimensionality reduction

Value

A list with the following components:

• tdt_measure The tree dimension value for the given input data

• tdt_effect Effect size for tree dimension

• leaves Number of leaf/degree1 vertices in the MST of the data

• diameter The tree diameter of MST, where each edge is of unit length

• original_dimension If "pca" is selected, the number of dimensions in the original dataset

• pca_components If "pca" is selected, the number of pca components selected after dimensionality reduction

• mst A vector of edges of the mst computed on x. Length of vector is always even.

TreeDimensionTest documentation built on March 18, 2022, 7:45 p.m.