depth.sample: Fast Depth Computation for Univariate and Bivariate Random...

In ddalpha: Depth-Based Classification and Calculation of Data Depth

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, [e-mail]

See Also

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 March 23, 2022, 9:07 a.m.