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Tukey depth

In statistics and computational geometry, the Tukey depth or half-space depth is a measure of the depth of a point in a fixed set of points. The concept is named after its inventor, John Tukey. Given a set of n points in d-dimensional space, Tukey's depth of a point x is the smallest fraction of points in any closed halfspace that contains x.

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In statistics and computational geometry, the Tukey depth 1 or half-space depth is a measure of the depth of a point in a fixed set of points. The concept is named after its inventor, John Tukey. Given a set of n points X n = { X 1 , , X n } {\displaystyle {\mathcal {X}}_{n}=\{X_{1},\dots ,X_{n}\}} in d-dimensional space, Tukey's depth of a point x is the smallest fraction (or number) of points in any closed halfspace that contains x.

Tukey's depth measures how extreme a point is with respect to a point cloud. It is used to define the bagplot, a bivariate generalization of the boxplot.

For example, for any extreme point of the convex hull there is always a (closed) halfspace that contains only that point, and hence its Tukey depth as a fraction is 1/n.

Definitions

Tukey's depth of a point x wrt to a point cloud. The blue region illustrates a halfspace containing x on the boundary. The halfspace is also a most extreme one so that it contains x but as few observations in the point cloud as possible. Thus, the proportion of points contained in this halfspace becomes the value of Tukey's depth for x. source ↗

Sample Tukey's depth of point x, or Tukey's depth of x with respect to the point cloud X n {\displaystyle {\mathcal {X}}_{n}} , is defined as

D ( x ; X n ) = inf v R d , v = 1 1 n i = 1 n 1 { v T ( X i x ) 0 } , {\displaystyle D(x;{\mathcal {X}}_{n})=\inf _{v\in \mathbb {R} ^{d},\|v\|=1}{\frac {1}{n}}\sum _{i=1}^{n}\mathbf {1} \{v^{T}(X_{i}-x)\geq 0\},}

where 1 { } {\displaystyle \mathbf {1} \{\cdot \}} is the indicator function that equals 1 if its argument holds true or 0 otherwise.

Population Tukey's depth of x wrt to a distribution P X {\displaystyle P_{X}} is

D ( x ; P X ) = inf v R d , v = 1 P ( v T ( X x ) 0 ) , {\displaystyle D(x;P_{X})=\inf _{v\in \mathbb {R} ^{d},\|v\|=1}P(v^{T}(X-x)\geq 0),}

where X is a random variable following distribution P X {\displaystyle P_{X}} .


Tukey mean and relation to centerpoint

A centerpoint c of a point set of size n is nothing else but a point of Tukey depth of at least n/(d + 1).

See also

See also

References

References

  1. Tukey, John W (1975). Mathematics and the Picturing of Data. Proceedings of the International Congress of Mathematicians. p. 523-531.