# append_mfData: Append two compatible multivariate functional datasets In roahd: Robust Analysis of High Dimensional Data

## Description

This is a convenience function that simplifies the task of appending multivariate functional observations of two datasets to a unique multivariate functional dataset.

## Usage

 `1` ```append_mfData(mfD1, mfD2) ```

## Arguments

 `mfD1` is the first multivariate functional dataset, stored into an `mfData` object. `mfD2` is the second multivariate functional dataset, stored into an `mfData` object.

## Details

The two original datasets must be compatible, i.e. must have same number of components (dimensions) and must be defined on the same grid. If we denote with X_1^(i), …, X_n^(i), i=0, …, L the first dataset, defined over the grid I = t_1, …, t_P, and with Y_1^(i), …, Y_m^(i), i=0, …, L the second functional dataset, the method returns the union dataset obtained by taking all the n + m observations together.

## Value

The function returns a `mfData` object containing the union of `mfD1` and `mfD2`

`append_fData`, `mfData`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```# Creating two simple bivariate datasets grid = seq(0, 2 * pi, length.out = 100) values11 = matrix( c(sin(grid), sin(2 * grid)), nrow = 2, ncol = length(grid), byrow=TRUE) values12 = matrix( c(sin(3 * grid), sin(4 * grid)), nrow = 2, ncol = length(grid), byrow=TRUE) values21 = matrix( c(cos(grid), cos(2 * grid)), nrow = 2, ncol = length(grid), byrow=TRUE) values22 = matrix( c(cos(3 * grid), cos(4 * grid)), nrow = 2, ncol = length(grid), byrow=TRUE) mfD1 = mfData( grid, list(values11, values12) ) mfD2 = mfData( grid, list(values21, values22) ) # Appending them to a unique dataset append_mfData(mfD1, mfD2) ```