Mixture Models for Spherical Data with Applications to Protein Bioinformatics

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Mardia, KV, Barber, S, Burdett, PM et al. (2 more authors) (2022) Mixture Models for Spherical Data with Applications to Protein Bioinformatics. In: SenGupta, A and Arnold, B, (eds.) Directional Statistics for Innovative Applications: A Bicentennial Tribute to Florence Nightingale. Forum for Interdisciplinary Mathematics . Springer Singapore , pp. 15-32. ISBN 978-9811910432



Copyright, Publisher and Additional Information: © 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at https://doi.org/10.1007/978-981-19-1044-9_2.
  • Accepted: 3 March 2022
  • Published: 16 June 2022
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 14:01
Last Modified: 07 Aug 2023 11:18
Status: Published
Publisher: Springer Singapore
Series Name: Forum for Interdisciplinary Mathematics
Identification Number: https://doi.org/10.1007/978-981-19-1044-9_2

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