This function implements a constructor for elements of S3
class
mfData
, aimed at implementing a representation of a multivariate
functional dataset.
1 
grid 
the (evenly spaced) grid over which the functional dataset is defined. 
Data_list 
a 
The functional dataset is represented as a collection of L
components,
each one an object of class fData
. Each component must contain elements
defined on the same grid as the others, and must contain the same number of
elements (N
).
The function returns a S3
object of class mfData
, containing
the following elements:
"N
": the number of elements in the dataset;
"L
": the number of components of the functional dataset;
"P
": the number of points in the 1D grid over which elements
are measured;
"t0
": the starting point of the 1D grid;
"tP
": the ending point of the 1D grid;
"fDList
": the list of fData
objects representing the
L
components as corresponding unviariate functional datasets.
fData
, generate_gauss_fdata
,
generate_gauss_mfdata
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22  # Defining parameters
N = 1e2
P = 1e3
t0 = 0
t1 = 1
# Defining the measurement grid
grid = seq( t0, t1, length.out = P )
# Generating an exponential covariance matrix to be used in the simulation of
# the functional datasets (see the related help for details)
C = exp_cov_function( grid, alpha = 0.3, beta = 0.4 )
# Simulating the measurements of two univariate functional datasets with
# required center and covariance function
Data_1 = generate_gauss_fdata( N, centerline = sin( 2 * pi * grid ), Cov = C )
Data_2 = generate_gauss_fdata( N, centerline = sin( 2 * pi * grid ), Cov = C )
# Building the mfData object
mfData( grid, list( Data_1, Data_2 ) )

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