ddalpha (version 1.3.16)

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)

Value

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

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.

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")