# depth.sample: Fast Depth Computation for Univariate and Bivariate Random... In ddalpha: Depth-Based Classification and Calculation of Data Depth

 depth.sample R Documentation

## Fast Depth Computation for Univariate and Bivariate Random Samples

### Description

Faster implementation of the halfspace and the simplicial depth. Computes the depth of a whole random sample of a univariate or a bivariate data in one run.

### Usage

``````depth.sample(A, B)
``````

### Arguments

 `A` Univariate or bivariate points whose depth is computed, represented by a matrix of size `m*2`. `m` stands for the number of points, `d` is 1 for univariate and 2 for bivariate data. `B` Random sample points with respect to which the depth of `A` is computed. `B` is represented by a matrix of size `n*2`, where `n` is the sample size.

### Details

The function returns vectors of sample halfspace and simplicial depth values.

### Value

Vector of length `m` of depth halfspace depth values is returned.

### Author(s)

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

`depth.halfspace`

`depth.simplicial`

### Examples

``````n = 100
m = 150
A = matrix(rnorm(2*n),ncol=2)
B = matrix(rnorm(2*m),ncol=2)
depth.sample(A,B)
system.time(D1<-depth.halfspace(A,B))
system.time(D2<-depth.sample(A,B))
max(D1-D2\$Half)

A = rnorm(100)
B = rnorm(150)
depth.sample(A,B)
# depth.halfspace(matrix(A,ncol=1),matrix(B,ncol=1))

``````

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