Description Usage Arguments Value See Also Examples
This method provides an easy and natural way to subset a multivariate
functional dataset stored in a mfData
object, without having to
deal with the inner representation of mfData
class.
1 2 | ## S3 method for class 'mfData'
mfD[i, j]
|
mfD |
the multivariate functional dataset in form of |
i |
a valid expression to subset rows ( observations ) of the univariate functional dataset. |
j |
a valid expression to subset columns ( measurements over the grid ) of the univariate functional dataset (must be contiguous). |
The method returns and mfData
object containing the
required subset ( both in terms of observations and measurement points ) of
the multivariate functional dataset.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | # 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
mfD = mfData( grid, list( Data_1, Data_2 ) )
# Subsetting the first 10 elements and 10 time points
mfD[1:10, 1:10]
# Subsetting only observations
mfD[1:10,]
# Subsetting only time points (contiguously)
mfD[,1:10]
|
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