Geometry-based Distance for Clustering Amino Acids

Abushilah, SF, Taylor, CC and Gusnanto, A (2020) Geometry-based Distance for Clustering Amino Acids. Journal of Applied Statistics, 47 (7). pp. 1235-1250. ISSN 0266-4763



Copyright, Publisher and Additional Information: © 2019, Informa UK Limited, trading as Taylor & Francis Group. This is an author produced version of a paper published in the Journal of Applied Statistics. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Circular distance, squared Euclidean distance, permutation two-sample test, energy statistic, hierarchical clustering, similarity indices
  • Accepted: 23 September 2019
  • Published (online): 3 October 2019
  • Published: 18 May 2020
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 11 Oct 2019 15:54
Last Modified: 27 Jan 2022 10:24
Status: Published
Publisher: Taylor and Francis
Identification Number: