---
title: "mfd"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{mfd}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
# The `mfd` class
Let us show how the `funcharts` package works through an example with the dataset `air`,
which has been included from the R package `FRegSigCom` and is used in the paper of Qi and Luo (2019).
## Getting multivariate functional data and the `mfd` class
We provide the `mfd` class for multivariate functional data.
It inherits from the `fd` class but provides some additional features:
* It forces the `coef` argument to be an array even when the number of functional observations and/or the number of functional variables are one
* It provides a better subset function `[` that never drops dimensions, then it always returns a `mfd` object with three-dimensional array argument `coef`; moreover it allows extracting observations/variables also by name
* When possible, it stores the original raw data in the long data frame format
The first thing is to get the `mfd` object from discrete data.
We currently allow two types of input with the two functions:
1. `get_mfd_data.frame`: first input must be a data.frame in the long format, with:
* one `arg` column giving the argument (`x`) values,
* one `id` column indicating the functional observation,
* one column per each functional variable indicating the corresponding `y` values
2. `get_mfd_list`: first input must be a list of matrices for the case all functional data are observed on the same grid, which:
* must have all the same dimension,
* have the variable names as name of the list,
* are such that, for each matrix:
* each row corresponds to a functional observation
* each column corresponds to a point on the grid
In this example, the dataset `air` is in the second format (list of matrices, with data observed on the same grid)
```r
library(funcharts)
data("air")
fun_covariates <- names(air)[names(air) != "NO2"]
mfdobj_x <- get_mfd_list(air[fun_covariates], grid = 1:24)
```
## Plotting functions
We also provide plotting functions based on `ggplot2` and `patchwork`.
```r
plot_mfd(mfdobj_x)
```
```r
plot_mfd(mfdobj_x[1:10, c("CO", "C6H6")])
```
