fdars (version 0.3.3)

fdata2pc: Convert Functional Data to Principal Component Scores

Description

Performs functional PCA and returns principal component scores for functional data. Uses SVD on centered data.

Usage

fdata2pc(fdataobj, ncomp = 2, lambda = 0, norm = TRUE)

Value

A list with components:

d

Singular values (proportional to sqrt of eigenvalues)

rotation

fdata object containing PC loadings

x

Matrix of PC scores (n x ncomp)

mean

Mean function (numeric vector)

fdataobj.cen

Centered fdata object

call

The function call

Arguments

fdataobj

An object of class 'fdata'.

ncomp

Number of principal components to extract (default 2).

lambda

Regularization parameter (default 0, not currently used).

norm

Logical. If TRUE (default), normalize the scores.

Examples

t <- seq(0, 1, length.out = 50)
X <- matrix(0, 20, 50)
for (i in 1:20) X[i, ] <- sin(2*pi*t) + rnorm(50, sd = 0.1)
fd <- fdata(X, argvals = t)
pc <- fdata2pc(fd, ncomp = 3)