A dynamic factor model for the analysis of multivariate time series

Citations

Cited by:

1. 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.
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. 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.
4. 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.
5. 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.
6. 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.
7. 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.
8. 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).
9. 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.
10. 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.
11. 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.
12. 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.
13. 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.
14. Stef Buuren, 1997. "Fitting arma time series by structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 215-236, June.
15. 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.
16. Sacha Epskamp, 2020. "Psychometric network models from time-series and panel data," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 206-231, March.
17. 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.
18. 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.
19. 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.
20. 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.
21. 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.
22. 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.
23. 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.
24. 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.
25. 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.
26. 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.
27. repec:dgr:rugsom:05f10 is not listed on IDEAS
28. 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.
29. 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).
30. 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.
31. 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.
32. 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.
33. 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.
34. 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.
35. 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).