IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v64y1999i1p91-94.html
   My bibliography  Save this article

Comment on fitting MA time series by structural equation models

Author

Listed:
  • Peter Molenaar

Abstract

No abstract is available for this item.

Suggested Citation

  • Peter Molenaar, 1999. "Comment on fitting MA time series by structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 64(1), pages 91-94, March.
  • Handle: RePEc:spr:psycho:v:64:y:1999:i:1:p:91-94
    DOI: 10.1007/BF02294322
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02294322
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/BF02294322?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. Peter Molenaar & Jan Gooijer & Bernhard Schmitz, 1992. "Dynamic factor analysis of nonstationary multivariate time series," Psychometrika, Springer;The Psychometric Society, vol. 57(3), pages 333-349, September.
    2. Peter Molenaar, 1985. "A dynamic factor model for the analysis of multivariate time series," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 181-202, 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. Peter Molenaar & John Nesselroade, 2001. "Rotation in the dynamic factor modeling of multivariate stationary time series," Psychometrika, Springer;The Psychometric Society, vol. 66(1), pages 99-107, March.
    2. Fei Gu & Kristopher J. Preacher & Emilio Ferrer, 2014. "A State Space Modeling Approach to Mediation Analysis," Journal of Educational and Behavioral Statistics, , vol. 39(2), pages 117-143, April.
    3. Nikolaos Zirogiannis & Yorghos Tripodis, 2018. "Dynamic factor analysis for short panels: estimating performance trajectories for water utilities," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(1), pages 131-150, March.
    4. Galeano, Pedro & Peña, Daniel, 2001. "Multivariate analysis in vector time series," DES - Working Papers. Statistics and Econometrics. WS ws012415, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Stef Buuren, 1997. "Fitting arma time series by structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 215-236, June.
    6. Carfora, Alfonso & Scandurra, Giuseppe & Thomas, Antonio, 2022. "Forecasting the COVID-19 effects on energy poverty across EU member states," Energy Policy, Elsevier, vol. 161(C).
    7. Montfort, Kees van & Bijleveld, Catrien, 1997. "Dynamic analysis of multivariate panel data with nonlinear transformations," Serie Research Memoranda 0054, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    8. Eichler, Michael & Motta, Giovanni & von Sachs, Rainer, 2011. "Fitting dynamic factor models to non-stationary time series," Journal of Econometrics, Elsevier, vol. 163(1), pages 51-70, July.
    9. Bouaddi, S. & Ihlal, A. & Fernández-García, A., 2017. "Comparative analysis of soiling of CSP mirror materials in arid zones," Renewable Energy, Elsevier, vol. 101(C), pages 437-449.
    10. Sy-Miin Chow & Guangjian Zhang, 2013. "Nonlinear Regime-Switching State-Space (RSSS) Models," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 740-768, October.
    11. Ortega, Jose Antonio & Poncela, Pilar, 2005. "Joint forecasts of Southern European fertility rates with non-stationary dynamic factor models," International Journal of Forecasting, Elsevier, vol. 21(3), pages 539-550.
    12. Daniel M. Smith & Theodore A. Walls, 2021. "Pursuing Collective Synchrony in Teams: A Regime-Switching Dynamic Factor Model of Speed Similarity in Soccer," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 1016-1038, December.
    13. Zachary F. Fisher & Younghoon Kim & Barbara L. Fredrickson & Vladas Pipiras, 2022. "Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 1-29, June.
    14. Xiaochun Jiang & Wei Sun & Peng Su & Ting Wang, 2019. "The Synergy of Financial Volatility between China and the United States and the Risk Conduction Paths," Sustainability, MDPI, vol. 11(15), pages 1-22, August.
    15. Lukoianove, Tatiana & Agarwal, James & Osiyevskyy, Oleksiy, 2022. "Modeling a country's political environment using dynamic factor analysis (DFA): A new methodology for IB research," Journal of World Business, Elsevier, vol. 57(5).
    16. Junhao Pan & Edward Haksing Ip & Laurette Dubé, 2020. "Multilevel Heterogeneous Factor Analysis and Application to Ecological Momentary Assessment," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 75-100, March.
    17. Peter Molenaar & Jan Gooijer & Bernhard Schmitz, 1992. "Dynamic factor analysis of nonstationary multivariate time series," Psychometrika, Springer;The Psychometric Society, vol. 57(3), pages 333-349, September.
    18. Shelley A. Blozis, 2022. "A Latent Variable Mixed-Effects Location Scale Model with an Application to Daily Diary Data," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1548-1570, December.
    19. Lyhagen, Johan, 2005. "The exact covariance matrix of dynamic models with latent variables," Statistics & Probability Letters, Elsevier, vol. 75(2), pages 133-139, November.
    20. Niansheng Tang & Sy-Miin Chow & Joseph G. Ibrahim & Hongtu Zhu, 2017. "Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 875-903, December.

    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:64:y:1999:i:1:p:91-94. 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.