negent3D: Maximizing negentropy for Q = 3 dimensions

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

Maximizing negentropy for Q = 3 dimensions

Description

Searches for the rotation that maximizes the estimated negentropy of the first column of the rotated data, and of the second variable fixing the first, for q = 3 dimensional data. The routine uses a random start for the function optim using the simulated annealing option SANN, hence one may wish to increase the number of attempts by setting nstart to a integer larger than 1.

Usage

negent3D(y, nstart = 1, m = 100, ...)

Arguments

y	The N \times 3 data matrix.
nstart	The number of times to randomly start the search routine.
m	The number of angles (between 0 and \pi) over which to search to find the second variables.
...	Further optional arguments to pass to the optim function to control the simulated annealing algorithm.

Value

A 'list' with the following components:

vectors

The 3 x 3 orthogonal matrix G that optimizes the negentropy.

values

Estimated negentropies for the three rotated variables, from largest to smallest.

See Also

negent, negent2D

Examples

## Not run: 
# Running this example will take approximately 30s.
# Centers and scales the variables.
y <- scale(as.matrix(iris[, 1:3]))

# Obtains Negent Vectors for 3x3 matrix
gstar <- negent3D(y, nstart = 100)$vectors

## End(Not run)

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