Principal Component Analysis for a Mix of Stationary and Nonstationary Variables
James D. Hamilton, Xinwei Ma, Jin Xi
National Bureau of Economic Research University of California San Diego
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摘要与影响
This paper develops a procedure for uncovering the common cyclical factors that drive a mix of stationary and nonstationary variables.The method does not require knowing which variables are nonstationary or the nature of the nonstationarity.An application to the FRED-MD macroeconomic dataset demonstrates that the approach offers similar benefits to those of traditional principal component analysis with some added advantages.
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化学Spectroscopy and Chemometric Analyses
Fault Detection and Control Systems · Statistical and numerical algorithms
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