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Latent variable analysis and partial correlation graphs for multivariate time series

We investigate the possibility of exploiting partial correlation graphs for identifying interpretable latent variables underlying a multivariate time series. It is shown how the collapsibility and separation properties of partial correlation graphs can be used to understand the relation between a factor model and the structure among the observable variables.
Year of publication:
2005
Authors: Fried, Roland ; Didelez, Vanessa
Published in:
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 73.2005, 3, p. 287-296
Publisher: Elsevier
Keywords: Time series analysis Dimension reduction Factor analysis Partial correlations
Type of publication: Article
Source:
Persistent link: https://www.econbiz.de/10005137918
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