dot_product | R Documentation |
The dimension of the original data set is n\*p
. It can be projected
onto a n\*k
space. The functions below are to provide such transformations, e.g.
the Andrews coefficient
(a Fourier transformation) and the Legendre
polynomials.
andrews(p = 4, k = 50 * (p - 1), ...) legendre(p = 4, k = 50 * (p - 1), ...)
p |
The number of dimensions |
k |
The sequence length |
... |
Other arguments passed on to methods. Mainly used for customized transformation function |
A list contains two named components
vector: A length k
vector (define the domain)
matrix: A p\*k
transformed coefficient matrix
Andrews, David F. "Plots of high-dimensional data." Biometrics (1972): 125-136.
Abramowitz, Milton, and Irene A. Stegun, eds. "Chapter 8" Handbook of mathematical functions with formulas, graphs, and mathematical tables. Vol. 55. US Government printing office, 1948.
x <- andrews(p = 4) dat <- iris[, -5] proj <- t(as.matrix(dat) %*% x$matrix) matplot(x$vector, proj, type = "l", lty = 1, col = "black", xlab = "x", ylab = "Andrews coefficients", main = "Iris")
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