Classification of form under heterogeneity and non-isotropic errors

Shuweihdi, F, Taylor, CC orcid.org/0000-0003-0181-1094 and Gusnanto, AS (2017) Classification of form under heterogeneity and non-isotropic errors. Journal of Applied Statistics, 44 (8). pp. 1495-1508. ISSN 0266-4763

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Authors/Creators:
Copyright, Publisher and Additional Information: (c) 2016, Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis in the Journal of Applied Statistics on 29 July 2016, available online: https://doi.org/10.1080/02664763.2016.1214246
Keywords: Data mining, classification, shape analysis, similarity, distance
Dates:
  • Published: 11 June 2017
  • Accepted: 14 July 2016
  • Published (online): 29 July 2016
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 27 Jan 2017 15:45
Last Modified: 03 Aug 2017 22:00
Published Version: https://doi.org/10.1080/02664763.2016.1214246
Status: Published
Publisher: Taylor & Francis
Identification Number: https://doi.org/10.1080/02664763.2016.1214246

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