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- Title
Latent factor model for multivariate functional data.
- Authors
Li, Ruonan; Xiao, Luo
- Abstract
For multivariate functional data, a functional latent factor model is proposed, extending the traditional latent factor model for multivariate data. The proposed model uses unobserved stochastic processes to induce the dependence among the different functions, and thus, for a large number of functions, may provide a more parsimonious and interpretable characterization of the otherwise complex dependencies between the functions. Sufficient conditions are provided to establish the identifiability of the proposed model. The performance of the proposed model is assessed through simulation studies and an application to electroencephalography data.
- Subjects
STOCHASTIC processes; ELECTROENCEPHALOGRAPHY; LATENT structure analysis; DATA modeling
- Publication
Biometrics, 2023, Vol 79, Issue 4, p3307
- ISSN
0006-341X
- Publication type
Article
- DOI
10.1111/biom.13924