IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v51y1986i2p285-311.html
   My bibliography  Save this article

Principal components analysis of sampled functions

Author

Listed:
  • Philippe Besse
  • J. Ramsay

Abstract

No abstract is available for this item.

Suggested Citation

  • Philippe Besse & J. Ramsay, 1986. "Principal components analysis of sampled functions," Psychometrika, Springer;The Psychometric Society, vol. 51(2), pages 285-311, June.
    • Handle: RePEc:spr:psycho:v:51:y:1986:i:2:p:285-311
    DOI: 10.1007/BF02293986
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02293986
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02293986?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. J. Ramsay, 1982. "When the data are functions," Psychometrika, Springer;The Psychometric Society, vol. 47(4), pages 379-396, December.
    2. Ledyard Tucker, 1958. "Determination of parameters of a functional relation by factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(1), pages 19-23, March.
    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. Mostafa Zahed & Trent Lalonde & Maryam Skafyan, 2023. "Application of an Intensive Longitudinal Functional Model with Multiple Time Scales in Objectively Measured Children’s Physical Activity," Mathematics, MDPI, vol. 11(8), pages 1-22, April.
    2. Cristhian Leonardo Urbano-Leon & Manuel Escabias & Diana Paola Ovalle-Muñoz & Javier Olaya-Ochoa, 2023. "Scalar Variance and Scalar Correlation for Functional Data," Mathematics, MDPI, vol. 11(6), pages 1-20, March.
    3. Piotr Tarka, 2018. "An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 313-354, January.
    4. Pennoni, Fulvia & Romeo, Isabella, 2016. "Latent Markov and growth mixture models for ordinal individual responses with covariates: a comparison," MPRA Paper 72939, University Library of Munich, Germany.
    5. Angel Calderon-Madrid & Alexandru Voicu, 2011. "The NAFTA tide: Lifting the larger and better boats," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 20(4), pages 467-505.
    6. Rhoden, Imke & Weller, Daniel & Voit, Ann-Katrin, 2021. "Spatio-temporal dynamics of European innovation: An exploratory approach via multivariate functional data cluster analysis," Ruhr Economic Papers 926, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    7. Zhenjie Liang & Futian Weng & Yuanting Ma & Yan Xu & Miao Zhu & Cai Yang, 2022. "Measurement and Analysis of High Frequency Assert Volatility Based on Functional Data Analysis," Mathematics, MDPI, vol. 10(7), pages 1-11, April.
    8. Kalogridis, Ioannis & Van Aelst, Stefan, 2023. "Robust penalized estimators for functional linear regression," Journal of Multivariate Analysis, Elsevier, vol. 194(C).
    9. Eldad Davidov & Stefan Thörner & Peter Schmidt & Stefanie Gosen & Carina Wolf, 2011. "Level and change of group-focused enmity in Germany: unconditional and conditional latent growth curve models with four panel waves," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 481-500, December.
    10. Mariano Valderrama, 2007. "An overview to modelling functional data," Computational Statistics, Springer, vol. 22(3), pages 331-334, September.
    11. Jeffrey R. Harring, 2009. "A Nonlinear Mixed Effects Model for Latent Variables," Journal of Educational and Behavioral Statistics, , vol. 34(3), pages 293-318, September.
    12. John Ross, 1966. "A remark on tucker and Messick's “points of view” analysis," Psychometrika, Springer;The Psychometric Society, vol. 31(1), pages 27-31, March.
    13. Jost Reinecke & Daniel Seddig, 2011. "Growth mixture models in longitudinal research," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 415-434, December.
    14. Wang, Bingling & Li, Yingxing & Härdle, Wolfgang Karl, 2022. "K-expectiles clustering," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    15. Jia Guo & Shiyan Ma & Xiang Li, 2022. "Exploring the Differences of Sustainable Urban Development Levels from the Perspective of Multivariate Functional Data Analysis: A Case Study of 33 Cities in China," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    16. Boente, Graciela & Fraiman, Ricardo, 2000. "Kernel-based functional principal components," Statistics & Probability Letters, Elsevier, vol. 48(4), pages 335-345, July.
    17. Jianping Zhu & Futian Weng & Muni Zhuang & Xin Lu & Xu Tan & Songjie Lin & Ruoyi Zhang, 2022. "Revealing Public Opinion towards the COVID-19 Vaccine with Weibo Data in China: BertFDA-Based Model," IJERPH, MDPI, vol. 19(20), pages 1-26, October.
    18. Philip A. White & Alan E. Gelfand, 2021. "Multivariate functional data modeling with time-varying clustering," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 586-602, September.
    19. Algimantas Birbilas & Alfredas Račkauskas, 2024. "Change-Point Detection in Functional First-Order Auto-Regressive Models," Mathematics, MDPI, vol. 12(12), pages 1-25, June.
    20. James Arbuckle & Michael Friendly, 1977. "On rotating to smooth functions," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 127-140, March.

    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:spr:psycho:v:51:y:1986:i:2:p:285-311. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.