# depth.: Calculate Depth In ddalpha: Depth-Based Classification and Calculation of Data Depth

 depth. R Documentation

## 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."`). `...` 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.

`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 May 29, 2024, 1:12 a.m.