depth.: Calculate Depth

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

Calculate Depth

Description

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

The detailed descriptions are found in the corresponding topics.

Usage

depth.(x, data, notion, ...)

## beta-skeleton depth
# depth.betaSkeleton(x, data, beta = 2, distance = "Lp", Lp.p = 2, 
#                   mah.estimate = "moment", mah.parMcd = 0.75)

## Tukey depth
# depth.halfspace(x, data, exact, method, num.directions = 1000, seed = 0)

## L2-depth
# depth.L2(x, data, mah.estimate = "moment", mah.parMcd = 0.75)

## Mahalanobis depth
# depth.Mahalanobis(x, data, mah.estimate = "moment", mah.parMcd = 0.75)

## projection depth
# depth.projection(x, data, method = "random", num.directions = 1000)

## simplicial depth
# depth.simplicial(x, data, exact = F, k = 0.05, seed = 0)

## simplicial volume depth
# depth.simplicialVolume(x, data, exact = F, k = 0.05, seed = 0)

## spatial depth
# depth.spatial(x, data)

## zonoid depth
# depth.zonoid(x, data)

## potential
# depth.potential (x, data, pretransform = "1Mom", 
#            kernel = "GKernel", kernel.bandwidth = NULL, mah.parMcd = 0.75)

## convex hull peeling depth
# depth.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.
notion	The name of the depth notion (shall also work with a user-defined depth function named "depth.<name>").
...	Additional parameters passed to the depth functions.

Value

Numerical vector of depths, one for each row in x; or one depth value if x is a numerical vector.

See Also

depth.betaSkeleton

depth.halfspace

depth.L2

depth.Mahalanobis

depth.projection

depth.simplicial

depth.simplicialVolume

depth.spatial

depth.zonoid

depth.potential

depth.qhpeeling

depth.graph for building the depth surfaces of the two dimensional data.

Examples

# 5-dimensional normal distribution
data <- mvrnorm(1000, rep(0, 5), 
                matrix(c(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),
                nrow = 5))
x <- mvrnorm(10, rep(1, 5), 
             matrix(c(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),
             nrow = 5))
                
depths <- depth.(x, data, notion = "zonoid")
cat("Depths: ", depths, "\n")

ddalpha documentation built on Oct. 1, 2024, 1:07 a.m.