Estimating Individual Mahalanobis Distance in High-Dimensional Data

Deliang Dai, Thomas Holgersson () and Peter Karlsson ()
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Thomas Holgersson: Linnaeus university, Jönköping university, & Centre of Excellence for Science and Innovation Studies (CESIS), Postal: SE 551 11, , Jönköping, , Sweden
Peter Karlsson: Linnaeus university & Jönköping university,, Postal: SE 551 11, , Jönköping, , Sweden

No 362, Working Paper Series in Economics and Institutions of Innovation from Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies

Abstract: This paper treats the problem of estimating individual Mahalanobis distances (MD) in cases when the dimension of the variable p is proportional to the sample size n. Asymptotic expected values are derived under the assumption p/n->c, 0

Keywords: Increasing dimension data; Mahalanobis distance; Inverse covariance matrix; Smoothing (search for similar items in EconPapers)
JEL-codes: C38 C46 C50 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2014-05-06
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:cesisp:0362

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