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A dynamic factor model for the analysis of multivariate time series

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Cited by:

  1. 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).
  2. Sacha Epskamp, 2020. "Psychometric network models from time-series and panel data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 206-231, March.
  3. Guangjian Zhang & Sy-Miin Chow & Anthony Ong, 2011. "A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series," Psychometrika, Springer;The Psychometric Society, vol. 76(1), pages 77-96, January.
  4. 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.
  5. 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.
  6. 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.
  7. Augustin Kelava & Pascal Kilian & Judith Glaesser & Samuel Merk & Holger Brandt, 2022. "Forecasting Intra-individual Changes of Affective States Taking into Account Inter-individual Differences Using Intensive Longitudinal Data from a University Student Dropout Study in Math," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 533-558, June.
  8. Timo Oertzen & Steven Boker, 2010. "Time Delay Embedding Increases Estimation Precision of Models of Intraindividual Variability," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 158-175, March.
  9. repec:dgr:rugsom:05f10 is not listed on IDEAS
  10. 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.
  11. 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.
  12. 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).
  13. Sun-Joo Cho & Sarah Brown-Schmidt & Paul De Boeck & Jianhong Shen, 2020. "Modeling Intensive Polytomous Time-Series Eye-Tracking Data: A Dynamic Tree-Based Item Response Model," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 154-184, March.
  14. 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.
  15. 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.
  16. Luke Mosley & Tak-Shing Chan & Alex Gibberd, 2023. "sparseDFM: An R Package to Estimate Dynamic Factor Models with Sparse Loadings," Papers 2303.14125, arXiv.org.
  17. 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.
  18. Ruofan Yu & Rong Chen & Han Xiao & Yuefeng Han, 2024. "Dynamic Matrix Factor Models for High Dimensional Time Series," Papers 2407.05624, arXiv.org.
  19. Sun-Joo Cho & Sarah Brown-Schmidt & Woo-yeol Lee, 2018. "Autoregressive Generalized Linear Mixed Effect Models with Crossed Random Effects: An Application to Intensive Binary Time Series Eye-Tracking Data," Psychometrika, Springer;The Psychometric Society, vol. 83(3), pages 751-771, September.
  20. Gilbert, Paul D. & Meijer, Erik, 2005. "Time Series Factor Analysis with an Application to Measuring Money," Research Report 05F10, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
  21. Galeano, Pedro, 2001. "Multivariate analysis in vector time series," DES - Working Papers. Statistics and Econometrics. WS ws012415, Universidad Carlos III de Madrid. Departamento de Estadística.
  22. 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.
  23. Xia, Ye-Mao & Tang, Nian-Sheng & Gou, Jian-Wei, 2016. "Generalized linear latent models for multivariate longitudinal measurements mixed with hidden Markov models," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 259-275.
  24. 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.
  25. Becker, Claudia & Fried, Roland, 2001. "Sliced inverse regression for high-dimensional time series," Technical Reports 2001,14, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  26. Marieke Timmerman & Henk Kiers, 2003. "Four simultaneous component models for the analysis of multivariate time series from more than one subject to model intraindividual and interindividual differences," Psychometrika, Springer;The Psychometric Society, vol. 68(1), pages 105-121, March.
  27. Stef Buuren, 1997. "Fitting arma time series by structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 215-236, June.
  28. Wei-Chun Hsu & Lin Lin & Chen-Yu Li, 2014. "Forecasting automobile sales: the Peña-Box approach," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(6), pages 568-580, August.
  29. Yao Zheng & H. Harrington Cleveland & Peter C. M. Molenaar & Kitty S. Harris, 2015. "An Alternative Framework to Investigating and Understanding Intraindividual Processes in Substance Abuse Recovery," Evaluation Review, , vol. 39(2), pages 229-254, April.
  30. 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.
  31. Katya C Fernandez & Aaron J Fisher & Cyrus Chi, 2017. "Development and initial implementation of the Dynamic Assessment Treatment Algorithm (DATA)," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-16, June.
  32. 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.
  33. M. Pilar Muñoz & Cristina Corchero & F.-Javier Heredia, 2013. "Improving Electricity Market Price Forecasting with Factor Models for the Optimal Generation Bid," International Statistical Review, International Statistical Institute, vol. 81(2), pages 289-306, August.
  34. 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.
  35. Guangjian Zhang & Michael Browne & Anthony Ong & Sy Chow, 2014. "Analytic Standard Errors for Exploratory Process Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 444-469, July.
  36. Nikolaos Zirogiannis & Kerry Krutilla & Yorghos Tripodis & Kathryn Fledderman, 2019. "Human Development Over Time: An Empirical Comparison of a Dynamic Index and the Standard HDI," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(2), pages 773-798, April.
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