High-dimensional computation of the deepest location.
type: Item
instance of: scholarly article
title: High-dimensional computation of the deepest location.
zbMATH Open document ID: 1046.62055
DOI: 10.1016/S0167-9473(99)00112-7
published in: Computational Statistics and Data Analysis
publication date: 2000-10-26T00:00:00Z
review text: The halfspace location depth of a point \(\theta\) relative to a data set \(X_{n}\) is defined as the smallest number of observations in any closed halfspace with boundary through \(\theta\). As such, halfspace depth can be seen as a kind of multivariate ranking. The deepest location, i.e., the \(\theta\) with maximal halfspace depth, is a multivariate generalization of the median. Until now the deepest location could only be computed for bivariate data. We construct an algorithm (called DEEPLOC) to approximate the deepest location in higher dimensions.
Mathematics Subject Classification ID: 62H05
Mathematics Subject Classification ID: 65C60
zbMATH DE Number: 1521872
zbMATH Keywords: Algorithm
zbMATH Keywords: location depth
zbMATH Keywords: multivariate median
author: Anja Struyf
author: Peter Rousseeuw
describes a project that uses: AS 307
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 1521872