Kent, JT orcid.org/0000-0002-1861-8349, Mardia, KV, Ippoliti, L et al. (1 more author) (2022) A Statistical Analysis of the Cardioid Radial Growth Model. In: Arnold, BC, Balakrishnan, N and Coelho, CA, (eds.) Methodology and Applications of Statistics: A Volume in Honor of C.R. Rao on the Occasion of his 100th Birthday. Contributions to Statistics . Springer , Cham, Switzerland , pp. 345-364. ISBN 978-3-030-83669-6
Abstract
A new two-parameter “full exponential cardioid” radial growth model for two-dimensional geometric objects is proposed and analyzed. The model depends additionally on two rotation parameters and on two seeds about which the growth is centered, plus a choice of three possible assumptions about statistical errors. If the seeds are assumed known, the remaining parameters can be estimated in closed form. Comparisons are given to earlier approaches. Two examples are given, one for a set of simulated data and one for a set of rat calvarial data.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG. This is an author produced version of a book chapter published in Methodology and Applications of Statistics. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Revised cardioid strain; Craniofacial growth; Deformation; Shape analysis; Outlines; Von mises distribution |
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: | 08 Apr 2022 11:33 |
Last Modified: | 01 Jan 2024 01:13 |
Published Version: | https://link.springer.com/chapter/10.1007/978-3-03... |
Status: | Published |
Publisher: | Springer |
Series Name: | Contributions to Statistics |
Identification Number: | 10.1007/978-3-030-83670-2_16 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185518 |