# depth: Depth calculation In DepthProc: Statistical Depth Functions for Multivariate Analysis

## Description

Depth calculation

## Usage

 `1` ```depth(u, X, method = "Projection", name = "X", threads = -1, ...) ```

## Arguments

 `u` Numerical vector or matrix whose depth is to be calculated. Dimension has to be the same as that of the observations. `X` The data as a matrix, data frame or list. If it is a matrix or data frame, then each row is viewed as one multivariate observation. If it is a list, all components must be numerical vectors of equal length (coordinates of observations). `method` Character string which determines the depth function. `method` can be "Projection" (the default), "Mahalanobis", "Euclidean" or "Tukey". For details see `depth.` `name` name for this data set - it will be used on plots. `threads` number of threads used in parallel computations. Default value -1 means that all possible cores will be used. `...` parameters specific to method - see `depthEuclid`

## Details

Calculate depth functions.

## Author(s)

Daniel Kosiorowski, Mateusz Bocian, Anna Wegrzynkiewicz and Zygmunt Zawadzki from Cracow University of Economics.

## References

Liu, R.Y., Parelius, J.M. and Singh, K. (1999), Multivariate analysis by data depth: Descriptive statistics, graphics and inference (with discussion), Ann. Statist., 27, 783-858.

Mosler K (2013). Depth statistics. In C Becker, R Fried, K S (eds.), Robustness and Complex Data Structures, Festschrift in Honour of Ursula Gather, pp. 17-34. Springer.

Rousseeuw, P.J. and Struyf, A. (1998), Computing location depth and regression depth in higher dimensions, Stat. Comput., 8, 193-203.

Zuo, Y. and Serfling, R. (2000), General Notions of Statistical Depth Functions, Ann. Statist., 28, no. 2, 461-482.

`depthContour` and `depthPersp` for depth graphics.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```require(robustbase) ## Calculation of Projection depth data(starsCYG, package = "robustbase") depth(t(colMeans(starsCYG)), starsCYG) #Aslo for matrices depth(starsCYG, starsCYG) ## Projection depth applied to a large bivariate data set x = matrix(rnorm(9999), nc = 3) depth(x, x) ```