| Dynamic factor analysis (DFA), a dimension-reduction technique and designed for time-series data, is useful for determining the contributions of explanatory variables and common trends to response variables. Compared with conventional multivariate analysis techniques, DFA takes into account the time component of the data and dominant explore latent variables. DFA ignored the process of pollution and received the reasonable model fitting. DFA has been successfully applied to aquatic ecological monitoring, ground water quality, and air pollution abroad; however, this technique has limited use in China. The development of DFA has broad prospect, such as self-improvement, application range, information mining, data preprocessing, forecasting analysis, and spatial analysis. With the development of environmental monitoring network, DFA will be extensively applied in China. |
