For a distribution $F$ on $\mathbb{R}^p$ and a point $x$ in $\mathbb{R}^p$, the simplical depth $D(x)$ is introduced, which is the probability that the point $x$ is contained inside a random simplex whose vertices are $p + 1$ independent observations from $F$. Mathematically and heuristically it is argued that $D(x)$ indeed can be viewed as a measure of depth of the point $x$ with respect to $F$. An empirical version of $D(\cdot)$ gives rise to a natural ordering of the data points from the center outward. The ordering thus obtained leads to the introduction of multivariate generalizations of the univariate sample median and $L$-statistics. This generalized sample median and $L$-statistics are affine equivariant.
@article{1176347507,
author = {Liu, Regina Y.},
title = {On a Notion of Data Depth Based on Random Simplices},
journal = {Ann. Statist.},
volume = {18},
number = {1},
year = {1990},
pages = { 405-414},
language = {en},
url = {http://dml.mathdoc.fr/item/1176347507}
}
Liu, Regina Y. On a Notion of Data Depth Based on Random Simplices. Ann. Statist., Tome 18 (1990) no. 1, pp. 405-414. http://gdmltest.u-ga.fr/item/1176347507/