# depthf.HR: Half-Region Depth for Functional Data In ddalpha: Depth-Based Classification and Calculation of Data Depth

 depthf.HR R Documentation

## Half-Region Depth for Functional Data

### Description

The half-region depth for functional real-valued data.

### Usage

``````depthf.HR(datafA, datafB, range = NULL, d = 101)
``````

### Arguments

 `datafA` Functions whose depth is computed, represented by a `dataf` object of their arguments and functional values. `m` stands for the number of functions. `datafB` Random sample functions with respect to which the depth of `datafA` is computed. `datafB` is represented by a `dataf` object of their arguments and functional values. `n` is the sample size. The grid of observation points for the functions `datafA` and `datafB` may not be the same. `range` The common range of the domain where the functions `datafA` and `datafB` are observed. Vector of length 2 with the left and the right end of the interval. Must contain all arguments given in `datafA` and `datafB`. `d` Grid size to which all the functional data are transformed. For depth computation, all functional observations are first transformed into vectors of their functional values of length `d` corresponding to equi-spaced points in the domain given by the interval `range`. Functional values in these points are reconstructed using linear interpolation, and extrapolation.

### Details

The function returns the vector of the sample half-region depth values.

### Value

A vector of length `m` of the half-region depth values.

### Author(s)

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

### References

Lopez-Pintado, S. and Romo, J. (2011). A half-region depth for functional data. Computational Statistics & Data Analysis 55 (4), 1679–1695.

### Examples

``````datafA = dataf.population()\$dataf[1:20]
datafB = dataf.population()\$dataf[21:50]
depthf.HR(datafA,datafB)
``````

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