Description Usage Arguments Details Value See Also Examples
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 univariate 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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