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Statistical Shape Methodology for the Analysis of Helices

Author

Listed:
  • Mai F. Alfahad

    (University of Leeds)

  • John T. Kent

    (University of Leeds)

  • Kanti V. Mardia

    (University of Leeds
    University of Oxford)

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.

Suggested Citation

  • Mai F. Alfahad & John T. Kent & Kanti V. Mardia, 2018. "Statistical Shape Methodology for the Analysis of Helices," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 8-32, December.
    • Handle: RePEc:spr:sankha:v:80:y:2018:i:1:d:10.1007_s13171-018-0144-8
    DOI: 10.1007/s13171-018-0144-8
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    References listed on IDEAS

    as
    1. K. V. Mardia, 1999. "Estimation of torsion," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(3), pages 373-381.
    2. Kanti V. Mardia, 2013. "Statistical approaches to three key challenges in protein structural bioinformatics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 62(3), pages 487-514, May.
    3. Kanti V. Mardia & Karthik Sriram & Charlotte M. Deane, 2018. "A statistical model for helices with applications," Biometrics, The International Biometric Society, vol. 74(3), pages 845-854, September.
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    Cited by:

    1. Kanti V. Mardia, 2021. "Comments on: Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 59-63, March.

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