动态因子分析在环境监测数据综合处理中的应用

动态因子分析(DFA)作为降维度的多元统计方法,被设计用于时间序列分析,以揭示多元变量中解释变量与共同趋势对响应变量的影响程度。相较传统多元统计方法,DFA显性考虑时间因素,并量化影响响应变量的潜在因素。该方法可以忽略内在理化过程,具有良好的模拟效果,且在国外已广泛应用于地表水及地下水生态环境、空气污染等领域,但在国内尚未被应用。DFA在自身完善、应用范围、信息挖掘、数据预处理、预测分析、空间分析方面仍有巨大发展前景。

Application of Dynamic Factor Analysis to Environmental Monitoring Data Processing

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.