Convex-hull-peeling depth#

qhpeeling(x, data)[source]#

Description

Calculates the convex hull peeling depth of points w.r.t. a multivariate data set.

Usage

qhpeeling(x, data)

Arguments

x

Matrix of objects (numerical vector as one object) whose depth is to be calculated; each row contains a d-variate point. Should have the same dimension as data.

data

Matrix of data where each row contains a d-variate point, w.r.t. which the depth is to be calculated.

References

• Barnett, V. (1976). The ordering of multivariate data. Journal of the Royal Statistical Society, Series A, 139, 318–355.

• Eddy, W. F. (1981). Graphics for the multivariate two-sample problem: Comment. Journal of the American Statistical Association, 76, 287–289.

Examples

>>> from depth.multivariate import *
>>> mat1=[[1, 0, 0, 0, 0],[0, 2, 0, 0, 0],[0, 0, 3, 0, 0],[0, 0, 0, 2, 0],[0, 0, 0, 0, 1]]
>>> mat2=[[1, 0, 0, 0, 0],[0, 1, 0, 0, 0],[0, 0, 1, 0, 0],[0, 0, 0, 1, 0],[0, 0, 0, 0, 1]]
>>> x = np.random.multivariate_normal([1,1,1,1,1], mat2, 10)
>>> data = np.random.multivariate_normal([0,0,0,0,0], mat1, 100)
>>> qhpeeling(x, data)
[0.   0.   0.   0.   0.   0.   0.01 0.   0.   0.01]