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")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.