sbp.fromABA: Build SBP Matrix of "Anti-Principal Balances"

In tpq/balance: Visualize Balances of Compositional Data

Description

This function builds an SBP of "anti-principal balances" by clustering the difference of the log-ratio variance from the maximum log-ratio variance. Unlike principal balances, where the first balances explain the most variance, this function selects "anti-principal balances" so that the last balances explain relatively more variance.

Usage

sbp.fromABA(x, alpha = NA)

Arguments

x	A matrix with rows as samples (N) and columns as components (D).
alpha	A double. Defines a hyper-parameter used by the Box-Cox transformation to approximate log-ratio variance in the presence of zeros. Skip with NA.

Value

An SBP matrix.

Author(s)

Thom Quinn

Examples

library(balance)
data(iris)
x <- iris[,1:4]
sbp.fromABA(x)

tpq/balance documentation built on Aug. 6, 2021, 10:45 p.m.