fdars (version 0.3.3)

fdata2pls: Convert Functional Data to PLS Scores

Description

Performs Partial Least Squares regression and returns component scores for functional data using the NIPALS algorithm.

Usage

fdata2pls(fdataobj, y, ncomp = 2, lambda = 0, norm = TRUE)

Value

A list with components:

weights

Matrix of PLS weights (m x ncomp)

scores

Matrix of PLS scores (n x ncomp)

loadings

Matrix of PLS loadings (m x ncomp)

call

The function call

Arguments

fdataobj

An object of class 'fdata'.

y

Response vector (numeric).

ncomp

Number of PLS 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)
y <- rowMeans(X) + rnorm(20, sd = 0.1)
fd <- fdata(X, argvals = t)
pls <- fdata2pls(fd, y, ncomp = 3)