Description Usage Arguments Value See Also Examples

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.

1 2 |

`x` |
the multivariate functional dataset whose cross-sectional mean must
be computed, in form of |

`...` |
possible additional parameters. This argument is kept for
compatibility with the |

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.

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 32 33 34 35 36 37 | ```
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)
``` |

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