IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v69y2004i2p257-273.html
   My bibliography  Save this article

Rotation to simple loadings using component loss functions: The orthogonal case

Author

Listed:
  • Robert Jennrich

Abstract

No abstract is available for this item.

Suggested Citation

  • Robert Jennrich, 2004. "Rotation to simple loadings using component loss functions: The orthogonal case," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 257-273, June.
    • Handle: RePEc:spr:psycho:v:69:y:2004:i:2:p:257-273
    DOI: 10.1007/BF02295943
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02295943
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02295943?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. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 187-200, September.
    2. Robert Jennrich, 2001. "A simple general procedure for orthogonal rotation," Psychometrika, Springer;The Psychometric Society, vol. 66(2), pages 289-306, June.
    3. Henk Kiers, 1994. "Simplimax: Oblique rotation to an optimal target with simple structure," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 567-579, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Conti, Gabriella & Frühwirth-Schnatter, Sylvia & Heckman, James J. & Piatek, Rémi, 2014. "Bayesian exploratory factor analysis," Journal of Econometrics, Elsevier, vol. 183(1), pages 31-57.
    2. Xinyi Liu & Gabriel Wallin & Yunxiao Chen & Irini Moustaki, 2023. "Rotation to Sparse Loadings Using $$L^p$$ L p Losses and Related Inference Problems," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 527-553, June.
    3. Shaobo Jin & Irini Moustaki & Fan Yang-Wallentin, 2018. "Approximated Penalized Maximum Likelihood for Exploratory Factor Analysis: An Orthogonal Case," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 628-649, September.
    4. Liu, Xinyi Lin & Wallin, Gabriel & Chen, Yunxiao & Moustaki, Irini, 2023. "Rotation to sparse loadings using Lp losses and related inference problems," LSE Research Online Documents on Economics 118349, London School of Economics and Political Science, LSE Library.
    5. Jin, Shaobo & Moustaki, Irini & Yang-Wallentin, Fan, 2018. "Approximated penalized maximum likelihood for exploratory factor analysis: an orthogonal case," LSE Research Online Documents on Economics 88118, London School of Economics and Political Science, LSE Library.
    6. Robert Boik, 2008. "Newton Algorithms for Analytic Rotation: an Implicit Function Approach," Psychometrika, Springer;The Psychometric Society, vol. 73(2), pages 231-259, June.
    7. Rosember Guerra-Urzola & Katrijn Van Deun & Juan C. Vera & Klaas Sijtsma, 2021. "A Guide for Sparse PCA: Model Comparison and Applications," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 893-919, December.
    8. Nickolay Trendafilov & Kohei Adachi, 2015. "Sparse Versus Simple Structure Loadings," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 776-790, September.

    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. Thomas Despois & Catherine Doz, 2022. "Identifying and interpreting the factors in factor models via sparsity : Different approaches," Working Papers halshs-03626503, HAL.
    2. Thomas Despois & Catherine Doz, 2023. "Identifying and interpreting the factors in factor models via sparsity: Different approaches," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 533-555, June.
    3. Urbano Lorenzo-Seva, 2000. "The weighted oblimin rotation," Psychometrika, Springer;The Psychometric Society, vol. 65(3), pages 301-318, September.
    4. Kohei Adachi, 2009. "Joint Procrustes Analysis for Simultaneous Nonsingular Transformation of Component Score and Loading Matrices," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 667-683, December.
    5. Liu, Xinyi Lin & Wallin, Gabriel & Chen, Yunxiao & Moustaki, Irini, 2023. "Rotation to sparse loadings using Lp losses and related inference problems," LSE Research Online Documents on Economics 118349, London School of Economics and Political Science, LSE Library.
    6. Yoshio Takane & Kwanghee Jung & Heungsun Hwang, 2010. "An acceleration method for Ten Berge et al.’s algorithm for orthogonal INDSCAL," Computational Statistics, Springer, vol. 25(3), pages 409-428, September.
    7. Rosember Guerra-Urzola & Katrijn Van Deun & Juan C. Vera & Klaas Sijtsma, 2021. "A Guide for Sparse PCA: Model Comparison and Applications," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 893-919, December.
    8. Urbano Lorenzo-Seva, 2003. "A factor simplicity index," Psychometrika, Springer;The Psychometric Society, vol. 68(1), pages 49-60, March.
    9. Marie Chavent & Vanessa Kuentz-Simonet & Jérôme Saracco, 2012. "Orthogonal rotation in PCAMIX," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(2), pages 131-146, July.
    10. Thomas Despois & Catherine Doz, 2022. "Identifying and interpreting the factors in factor models via sparsity : Different approaches," PSE Working Papers halshs-03626503, HAL.
    11. Ikemoto, Hiroki & Adachi, Kohei, 2016. "Sparse Tucker2 analysis of three-way data subject to a constrained number of zero elements in a core array," Computational Statistics & Data Analysis, Elsevier, vol. 98(C), pages 1-18.
    12. Kohei Adachi, 2011. "Three-Way Tucker2 Component Analysis Solutions of Stimuli × Responses × Individuals Data with Simple Structure and the Fewest Core Differences," Psychometrika, Springer;The Psychometric Society, vol. 76(2), pages 285-305, April.
    13. Robert Jennrich, 2006. "Rotation to Simple Loadings Using Component Loss Functions: The Oblique Case," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 173-191, March.
    14. Xinyi Liu & Gabriel Wallin & Yunxiao Chen & Irini Moustaki, 2023. "Rotation to Sparse Loadings Using $$L^p$$ L p Losses and Related Inference Problems," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 527-553, June.
    15. Guerra Urzola, Rosember & Van Deun, Katrijn & Vera, J. C. & Sijtsma, K., 2021. "A guide for sparse PCA : Model comparison and applications," Other publications TiSEM 4d35b931-7f49-444b-b92f-a, Tilburg University, School of Economics and Management.
    16. Bonhomme, Stphane & Robin, Jean-Marc, 2009. "Consistent noisy independent component analysis," Journal of Econometrics, Elsevier, vol. 149(1), pages 12-25, April.
    17. Fernando Castelló-Sirvent & Pablo Pinazo-Dallenbach, 2021. "Corruption Shock in Mexico: fsQCA Analysis of Entrepreneurial Intention in University Students," Mathematics, MDPI, vol. 9(14), pages 1-31, July.
    18. Matkovskyy, Roman, 2013. "To the Problem of Financial Safety Estimation: the Index of Financial Safety of Turkey," MPRA Paper 47673, University Library of Munich, Germany.
    19. Jha, Raghbendra & Murthy, K. V. Bhanu, 2003. "An inverse global environmental Kuznets curve," Journal of Comparative Economics, Elsevier, vol. 31(2), pages 352-368, June.
    20. Rodríguez-Fuentes, Carlos Javier & Hernández-López, Montserrat, 1997. "Análisis de diferencias estructurales interregionales determinantes en el impacto de la política monetaria," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 7, pages 141-157, Junio.

    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:69:y:2004:i:2:p:257-273. 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.