IDEAS home Printed from https://ideas.repec.org/a/bla/scjsta/v41y2014i1p10-11.html
   My bibliography  Save this article

Contribution to the Discussion of the Paper Geodesic Monte Carlo on Embedded Manifolds

Author

Listed:
  • John T. Kent

Abstract

No abstract is available for this item.

Suggested Citation

  • John T. Kent, 2014. "Contribution to the Discussion of the Paper Geodesic Monte Carlo on Embedded Manifolds," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 10-11, March.
    • Handle: RePEc:bla:scjsta:v:41:y:2014:i:1:p:10-11
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/sjos.12068
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Peter J. Green & Kanti V. Mardia, 2006. "Bayesian alignment using hierarchical models, with applications in protein bioinformatics," Biometrika, Biometrika Trust, vol. 93(2), pages 235-254, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Di Noia, Antonio & Mastrantonio, Gianluca & Jona Lasinio, Giovanna, 2024. "Bayesian size-and-shape regression modelling," Statistics & Probability Letters, Elsevier, vol. 204(C).
    2. Ejlali Nasim & Faghihi Mohammad Reza & Sadeghi Mehdi, 2017. "Bayesian comparison of protein structures using partial Procrustes distance," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(4), pages 243-257, September.
    3. Ian L. Dryden & Jonathan D. Hirst & James L. Melville, 2007. "Statistical Analysis of Unlabeled Point Sets: Comparing Molecules in Chemoinformatics," Biometrics, The International Biometric Society, vol. 63(1), pages 237-251, March.
    4. Angela Andreella & Livio Finos, 2022. "Procrustes Analysis for High-Dimensional Data," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1422-1438, December.
    5. Kanti Mardia, 2010. "Bayesian analysis for bivariate von Mises distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(3), pages 515-528.
    6. S.M. Najibi & M.R. Faghihi & M. Golalizadeh & S.S. Arab, 2015. "Bayesian alignment of proteins via Delaunay tetrahedralization," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 1064-1079, May.
    7. Su, J. & Srivastava, A. & Huffer, F.W., 2013. "Detection, classification and estimation of individual shapes in 2D and 3D point clouds," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 227-241.
    8. Mitsunori Kayano & Koji Dozono & Sadanori Konishi, 2010. "Functional Cluster Analysis via Orthonormalized Gaussian Basis Expansions and Its Application," Journal of Classification, Springer;The Classification Society, vol. 27(2), pages 211-230, September.
    9. Nieto, Carmen, 2007. "Spatial matching of M configurations of points with a bioinformatics application," DES - Working Papers. Statistics and Econometrics. WS ws070903, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Michael Habeck, 2009. "Generation of three-dimensional random rotations in fitting and matching problems," Computational Statistics, Springer, vol. 24(4), pages 719-731, December.
    11. Athanasios Micheas & Yuqiang Peng, 2010. "Bayesian Procrustes analysis with applications to hydrology," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(1), pages 41-55.
    12. Angela Andreella & Riccardo Santis & Anna Vesely & Livio Finos, 2023. "Procrustes-based distances for exploring between-matrices similarity," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(3), pages 867-882, September.
    13. Nieto, Carmen, 2008. "Bayesian non-linear matching of pairwise microarray gene expressions," DES - Working Papers. Statistics and Econometrics. WS ws082507, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Kanti V. Mardia & Vysaul B. Nyirongo & Christopher J. Fallaize & Stuart Barber & Richard M. Jackson, 2011. "Hierarchical Bayesian Modeling of Pharmacophores in Bioinformatics," Biometrics, The International Biometric Society, vol. 67(2), pages 611-619, June.
    15. Ian L. Dryden & Kwang-Rae Kim & Huiling Le, 2019. "Bayesian Linear Size-and-Shape Regression with Applications to Face Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 83-103, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:scjsta:v:41:y:2014:i:1:p:10-11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0303-6898 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.