onlinePCA (version 1.3.1)

coef2fd: Recover functional data from their B-spline coefficients

Description

This function computes functional data from their coefficients in a B-spline basis.

Usage

coef2fd(beta, basis, byrow = TRUE)

Value

A matrix of functional data stored in the same format (row or columns) as the coefficients beta.

Arguments

beta

B-spline coefficients

basis

object created by create.basis

byrow

are the coefficients of each functional observation stored in rows (TRUE) or in columns (FALSE)?

See Also

create.basis, fd2coef

Examples

Run this code
n <- 100 # number of curves
d <- 500 # number of observation points
grid <- (1:d)/d # observation points
p <- 50 # number of B-spline basis functions 

# Simulate Brownian motion
x <- matrix(rnorm(n*d,sd=1/sqrt(d)),n,d)
x <- t(apply(x,1,cumsum))

# Create B-spline basis 
mybasis <- create.basis(grid, p, 1e-4)

# Compute smooth basis coefficients 
beta <- fd2coef(x, mybasis)

# Recover smooth functional data
x.smooth <- coef2fd(beta, mybasis) 
	
# Standard PCA and Functional PCA
pca <- prcomp(x)
fpca <- prcomp(beta)

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