negent2D: Maximizing negentropy for q = 2 dimensions

In coatless/msos: Data Sets and Functions Used in Multivariate Statistics: Old School by John Marden

Maximizing negentropy for q = 2 dimensions

Description

Searches for the rotation that maximizes the estimated negentropy of the first column of the rotated data, for q = 2 dimensional data.

Usage

negent2D(y, m = 100)

Arguments

y	The n \times 2 data matrix.
m	The number of angles (between 0 and \pi) over which to search.

Value

A list with the following components:

vectors

The 2 ? 2 orthogonal matrix G that optimizes the negentropy.

values

Estimated negentropies for the two rotated variables. The largest is first.

See Also

negent, negent3D

Examples

# Load iris data
data(iris)

# Centers and scales the variables.
y <- scale(as.matrix(iris[, 1:2]))

# Obtains Negent Vectors for 2 x 2 matrix
gstar <- negent2D(y, m = 10)$vectors

coatless/msos documentation built on Nov. 16, 2023, 5:31 a.m.