# Cmetric: Fast Computation of the Uniform Metric for Sets of Functional... In ddalpha: Depth-Based Classification and Calculation of Data Depth

 Cmetric R Documentation

## Fast Computation of the Uniform Metric for Sets of Functional Data

### Description

Returns the matrix of `C` (uniform) distances between two sets of functional data.

### Usage

``````Cmetric(A, B)
``````

### Arguments

 `A` Functions of the first set, represented by a matrix of their functional values of size `m*d`. `m` stands for the number of functions, `d` is the number of the equi-distant points in the domain of the data at which the functional values of the `m` functions are evaluated. `B` Functions of the second set, represented by a matrix of their functional values of size `n*d`. `n` stands for the number of functions, `d` is the number of the equi-distant points in the domain of the data at which the functional values of the `n` functions are evaluated. The grid of observation points for the functions `A` and `B` must be the same.

### Details

For two sets of functional data of sizes `m` and `n` represented by matrices of their functional values, this function returns the symmetric matrix of size `m*n` whose entry in the `i`-th row and `j`-th column is the approximated `C` (uniform) distance of the `i`-th function from the first set, and the `j`-th function from the second set. This function is utilized in the computation of the h-mode depth.

### Value

A symmetric matrix of the distances of the functions of size `m*n`.

### Author(s)

Stanislav Nagy, nagy@karlin.mff.cuni.cz

`depthf.hM`

`dataf2rawfd`

### Examples

``````datapop = dataf2rawfd(dataf.population()\$dataf,range=c(1950,2015),d=66)
A = datapop[1:20,]
B = datapop[21:50,]
Cmetric(A,B)

``````

ddalpha documentation built on May 29, 2024, 1:12 a.m.