Abstract

NIR news
Volume 21 Issue 1, Pages 12–14 (2010)
doi: 10.1255/nirn.1167

Mahalanobis and Euclidean distances

Tom Fearn
Department of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK

This issue's Chemometrics space was sparked by two independent recent queries about the use of Mahalanobis distance for detecting outliers. It discusses how, for NIR data, the Euclidean distance is preference, but the need for dimension reduction complicates matters.

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