向量自回归模型，可以用于分析多元时间序列相关关系，进行格兰杰因果检验、脉冲响应等等

ARIMAX模型检验 适应性检验:模型残差序列属于白噪声序列；残差与输入变量序列无显著关系 参数检验:所有参数显著非0 back

时间序列的建模过程，主要是ARMA和ARIMA等模型的建模。

蔡瑞胸的<>中文版，带书签

华章数学译丛59 多元时间序列分析及金融应用 R语言 中英文

Multivariate time series analysis considers simultaneously multiple time series. It is a branch of multivariate statistical analysis but deals specifically with dependent data. It is, in general, much more complicated than the univariate time series analysis, especially when the number of series considered is large. We study this more complicated statistical analysis in this book because in real life decisions often involve multiple inter-related factors or variables. Understanding the relationships between those factors and providing accurate predictions of those variables are valuable in decision making. The objectives of multivariate time series analysis thus include 1. To study the dynamic relationships between variables 2. To improve the accuracy of prediction