Elastic PCR Attribution

Decomposes prediction importance into amplitude and phase contributions after elastic PCR.

Usage

elastic.attribution(
  fdataobj,
  y,
  ncomp = 3,
  pca.method = c("vertical", "horizontal", "joint"),
  lambda = 0,
  max.iter = 20,
  tol = 1e-04,
  n.perm = 100,
  seed = NULL
)

Arguments

fdataobj

An fdata object.

y

Response vector.

ncomp

Number of elastic FPCA components.

pca.method

PCA method: "vertical", "horizontal", or "joint".

lambda

Regularization for alignment (default 0).

max.iter

Maximum alignment iterations (default 20).

tol

Convergence tolerance (default 1e-4).

n.perm

Number of permutations (default 100).

seed

Random seed.

Value

A list with amplitude_r_squared, phase_r_squared, total_r_squared, amplitude_importance, phase_importance, and p_values.

Examples

# \donttest{
fd <- fdata(matrix(rnorm(500), nrow = 50), argvals = seq(0, 1, length.out = 10))
y <- rnorm(50)
result <- elastic.attribution(fd, y, ncomp = 3)
# }