funData: 'S3' Class for functional datasets. A class for univariate or...
In martinoandrea92/dpdistance: Inference and Clustering of Functional Data

Description Usage Arguments Value See Also Examples

S3 Class for functional datasets. A class for univariate or multivariate functional dataset.

1	funData(grid, data)

`grid`	the grid (of length `T`) over which the functional dataset is defined.
`data`	a vector, a matrix or a `list` of `d` vectors or matrices containing the functional data.

The function returns a S3 object of class funData, containing the grid over which the functional dataset is defined and a matrix or a list of d matrices containing the functional data

simulate_KL

# Define parameters
n <- 50
P <- 100
K <- 150

# Grid of the functional dataset
t <- seq( 0, 1, length.out = P )

# Define the means and the parameters to use in the simulation
# with the Karhunen - LoÃ¨ve expansion
m1 <- t^2 * ( 1 - t )
m2 <- t * ( 1 - t )^2

lambda <- rep( 0, K )
theta <- matrix( 0, K, P )
for ( k in 1:K) {
  lambda[k] <- 1 / ( k + 1 )^2
  if ( k%%2 == 0 )
    theta[k, ] <- sqrt( 2 ) * sin( k * pi * t )
  else if ( k%%2 != 0 && k != 1 )
    theta[k, ] <- sqrt( 2 ) * cos( ( k - 1 ) * pi * t )
  else
    theta[k, ] <- rep( 1, P )
}
# Simulate the functional data
x1 <- simulate_KL( t, n, m1, rho = lambda, theta = theta )
x2 <- simulate_KL( t, n, m2, rho = lambda, theta = theta )

FD <- funData( t, list( x1, x2 ) )