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A general dynamic factor model for multivariate nonstationary processes which simultaneously takes into account the time-lagged correlations and the linear trends of time series is developed. The distinct advantages of this model are the reduction of high dimensionality of original variables, the facilitation of direct estimation of the linear trends, and its capability for forecasting. Application...
A sample covariance matrix of water quality constituents measured at a fixed station on a river is used as a basis for building a general structural equation model which relates observed and latent (unobserved) variables and provides information for identifying and explaining the effects of the latent factors.
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