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Searches for the rotation that maximizes the estimated negentropy of the first column of the rotated data, for \(q = 2\) dimensional data.
negent2D(y, m = 100)
The \(n \times 2\) data matrix.
The number of angles (between \(0\) and \(\pi\)) over which to search.
A list with the following components:
The \(2 ? 2\) orthogonal matrix G that optimizes the negentropy.
Estimated negentropies for the two rotated variables. The largest is first.
negent, negent3D
negent
negent3D
# NOT RUN { # 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 # }
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