This S3
method implements the cross-sectional mean of a
multivariate functional dataset stored in a mfData
object, i.e. the
mean computed point-by-point along the grid over which the dataset is
defined.
# S3 method for mfData
mean(x, ...)
the multivariate functional dataset whose cross-sectional mean must
be computed, in form of mfData
object.
possible additional parameters. This argument is kept for
compatibility with the S3
definition of mean
, but it is not
actually used.
The function returns a mfData
object with one observation
defined on the same grid as the argument x
's representing the
desired cross-sectional mean.
N = 1e2
L = 3
P = 1e2
grid = seq( 0, 1, length.out = P )
# Generating a gaussian functional sample with desired mean
target_mean = sin( 2 * pi * grid )
C = exp_cov_function( grid, alpha = 0.2, beta = 0.2 )
# Independent components
correlations = c( 0, 0, 0 )
mfD = mfData( grid,
generate_gauss_mfdata( N, L,
correlations = correlations,
centerline = matrix( target_mean,
nrow = 3,
ncol = P,
byrow = TRUE ),
listCov = list( C, C, C ) )
)
# Graphical representation of the mean
oldpar <- par(mfrow = c(1, 1))
par(mfrow = c(1, L))
for(iL in 1:L)
{
plot(mfD$fDList[[iL]])
plot(
mean(mfD)$fDList[[iL]],
col = 'black',
lwd = 2,
lty = 2,
add = TRUE
)
}
par(oldpar)