期刊
BIOMETRIKA
卷 95, 期 2, 页码 365-379出版社
OXFORD UNIV PRESS
DOI: 10.1093/biomet/asn009
关键词
cross-correlation function; dimension reduction; factor model; multivariate time series; nonstationarity; portmanteau test; white noise
资金
- Engineering and Physical Sciences Research Council [EP/C549058/1] Funding Source: researchfish
We propose a new method for estimating common factors of multiple time series. One distinctive feature of the new approach is that it is applicable to some nonstationary time series. The unobservable, nonstationary factors are identified by expanding the white noise space step by step, thereby solving a high-dimensional optimization problem by several low-dimensional sub-problems. Asymptotic properties of the estimation are investigated. The proposed methodology is illustrated with both simulated and real datasets.
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