fdasrvf (version 2.3.6)

curve_principal_directions: Curve PCA

Description

Calculate principal directions of a set of curves

Usage

curve_principal_directions(v, K, mu, len = NA, no = 3, N = 5, mode = "O")

Value

Returns a list containing

s

singular values

U

singular vectors

coef

principal coefficients

pd

principal directions

Arguments

v

array of sizes \(n \times T \times N1\) for \(N1\) shooting vectors of dimension \(n\) evaluated on a grid of \(T\) points

K

matrix of sizes \(nT \times nT\) of covariance matrix

mu

matrix of sizes \(n \times T\) of mean srvf

len

length of original curves (default = NA)

no

number of components

N

number of samples on each side of mean

mode

Open ("O") or Closed ("C") curves

References

Srivastava, A., Klassen, E., Joshi, S., Jermyn, I., (2011). Shape analysis of elastic curves in euclidean spaces. Pattern Analysis and Machine Intelligence, IEEE Transactions on 33 (7), 1415-1428.

Examples

out <- curve_karcher_mean(beta[, , 1, 1:2], maxit = 2)
# note: use more shapes, small for speed
K <- curve_karcher_cov(out$v)
out <- curve_principal_directions(out$v, K, out$mu)