Dynamic factor analysis to estimate common trends in fisheries time series

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MARSS: Multivariate Autoregressive State-space Models for Analyzing Time-series Data (2012, unknown): “DFA has been applied in a number of fields (e.g. Harvey, 1989) and can be thought of as a principal components analysis for time-series data (Zuur et al., 2003a,b).”
The Causes and Consequences of Compensatory Dynamics in Ecological Communities (2009, background): “These methods can extract and identify multiple common trends from time series to evaluate interactions between response variables and to determine the effects of environmental explanatory variables (Solow 1994; Zuur et al. 2003a,b).”
Selective drought-induced decline of pine species in southeastern Spain (2012, methodology): “2.7 Dynamic factor analysis Dynamic factor analysis (DFA) is a technique used to detect and estimate underlying common trends in multivariate time series (see a description of the method in Zuur et al. 2003 and the Supporting Information).”
Joint dynamic species distribution models: a tool for community ordination and spatio‐temporal monitoring (2016, methodology): “There is a long history of using DFA in the analyses of multivariate time-series data in economics (Harvey, 1990) and medicine (Molenaar, 1985) but it is relatively new to ecology (Zuur et al ., 2003).”