This function performs the plot of a functional multivariate dataset stored
in an object of class mfData
. It is able to accept all the usual
customizable graphical parameters, otherwise it will use the default ones.
# S3 method for mfData
plot(x, ...)
the multivariate functional dataset in form of mfData
object.
additional graphical parameters to be used in plotting functions
(see Details
for the use of ylab
and main
).
The current active graphical device is split into a number of sub-figures,
each one meant to contain the plot of the corresponding dimension of the
mfData
object. In particular, they are arranged in a rectangular
lattice with a number of rows equal to \( \lfloor \sqrt{ L } \rfloor \)
and a number of columns equal to \( \lceil L / \lfloor \sqrt{L} \rfloor
\rceil \).
A special use of the graphical parameters allows to set up y-labels and
titles for all the sub-figures in the graphical window. In particular,
parameters ylab
and main
can take as argument either a single
string, that are repeatedly used for all the sub-graphics, or a list of
different strings (one for each of the L
dimensions) that have to be
used in the corresponding graphic.
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 and plotting tt
plot( mfData( grid, list( Data_1, Data_2 ) ),
xlab = 'time', ylab = list( '1st dim.', '2nd dim.' ),
main = list( 'An important plot here', 'And another one here' ) )