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CCCG
1998

Quantile approximation for robust statistical estimation

14 years 24 days ago
Quantile approximation for robust statistical estimation
Given a set P of n points in Rd, a fundamental problem in computational geometry is 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.
David M. Mount, Nathan S. Netanyahu, Christine D.
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 1998
Where CCCG
Authors David M. Mount, Nathan S. Netanyahu, Christine D. Piatko, Ruth Silverman, Angela Y. Wu
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