@article {15607,
	title = {Quantile approximation for robust statistical estimation and k-enclosing problems},
	journal = {International Journal of Computational Geometry and Applications},
	volume = {10},
	year = {2000},
	month = {2000///},
	pages = {593 - 608},
	abstract = {Given a set P of n points in Rd, a fundamental problem in computational geometryis concerned with finding the smallest shape of some type that encloses all the points
of P. Well-known instances of this problem include finding the smallest enclosing box,
minimum volume ball, and minimum volume annulus. In this paper we consider the
following variant: Given a set of n points in Rd, find the smallest shape in question that
contains at least k points or a certain quantile of the data. This type of problem is known
as a k-enclosing problem. We present a simple algorithmic framework for computing
quantile approximations for the minimum strip, ellipsoid, and annulus containing a given
quantile of the points. The algorithms run in O(n log n) time.
},
	author = {Mount, Dave and Netanyahu,N. S and Piatko,C. D and Silverman,R. and Wu,A. Y}
}
