Description Usage Arguments Value See Also Examples

This method provides an easy and natural way to subset a functional dataset
stored in a `fData`

object, without having to deal with the inner
representation of `fData`

class.

1 2 | ```
## S3 method for class 'fData'
fD[i, j, as_fData = TRUE]
``` |

`fD` |
the univariate 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). |

`as_fData` |
logical flag to specify whether the output should be returned
as an |

The method returns either an `fData`

object ( if ```
as_fData
= TRUE
```

) or a `matrix`

( if `as_fData = FALSE `

) containing the
required subset ( both in terms of observations and measurement points ) of
the univariate 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 32 33 34 35 36 37 | ```
N = 20
P = 1e2
# One dimensional grid
grid = seq( 0, 1, length.out = P )
# Generating an exponential covariance function (see related help for more
# information )
C = exp_cov_function( grid, alpha = 0.3, beta = 0.4 )
# Generating a synthetic dataset with a gaussian distribution and
# required mean and covariance function:
fD = fData( grid,
generate_gauss_fdata( N,
centerline = sin( 2 * pi * grid ),
Cov = C ) )
dev.new()
oldpar <- par(mfrow = c(1, 1))
par(mfrow = c(2, 2))
# Original data
plot(fD)
# Subsetting observations
plot(fD[c(1, 2, 3), , as_fData = TRUE])
# Subsetting measurements
plot(fD[, 1:30])
# Subsetting both observations and measurements
plot(fD[1:10, 50:P])
par(oldpar)
# Subsetting both observations and measurements but returning a matrix
fD[1:10, 50:P, as_fData = FALSE]
``` |

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