A novel algorithm for dynamic factor analysis
Resource
Applied Mathematics and Computation 175 (2): 1288-1297
Journal
Applied Mathematics and Computation
Journal Volume
175
Journal Issue
2
Pages
1288-1297
Date Issued
2006
Date
2006
Author(s)
Abstract
In this paper, a dynamic factor model is proposed to extract the dynamic factors from time series data. In order to deal with the problem of scaling, the cross-correlation matrices (CCM) are first employed to cluster the time series data. Then, the dynamic factors are extracted using the revised independent component analysis (ICA). In addition, a numerical study is used to demonstrate the proposed method. On the basis of the simulated results, we can conclude that the proposed method can really extract the effective dynamic factors. © 2005 Elsevier Inc. All rights reserved.
Subjects
Cross-correlation matrices (CCM); Dynamic factor model; Factor analysis; Independent component analysis (ICA); Time series
Other Subjects
Algorithms; Computer simulation; Independent component analysis; Numerical methods; Problem solving; Time series analysis; Cross-correlation matrices (CCM); Dynamic factor models; Factor analysis; Time series data; Dynamic programming
Type
journal article
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