Alfahad, MF, Kent, JT orcid.org/0000-0002-1861-8349 and Mardia, KV (2018) Statistical shape methodology for the analysis of helices. Sankhya A: The Indian Journal of Statistics, 80 (Suppl 1). pp. 8-32. ISSN 0976-836X
Abstract
Consider a helix in three-dimensional space along which a sequence of equally spaced points is observed, subject to statistical noise. For data coming from a single helix, a two-stage algorithm based on a profile likelihood is developed to compute the maximum likelihood estimate of the helix parameters. Statistical properties of the estimator are studied and comparisons are made to other estimators found in the literature. Next a likelihood ratio test is developed to test if there is a change point in the helix, splitting the data into two sub-helices. The shapes of protein α-helices are used to illustrate the methodology.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Keywords: | Change point; Helix axis; Kinked helix; Principal component analysis; Procrustes analysis; Shape analysis |
Dates: |
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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: | 06 Nov 2018 15:00 |
Last Modified: | 25 Jun 2023 21:34 |
Status: | Published |
Publisher: | Springer India |
Identification Number: | 10.1007/s13171-018-0144-8 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:138207 |
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