Multiple Time Series Modeling and Extended Sample Cross-Correlations
介绍多元自回归移动平均模型，提出一种扩展样本互相关方法用于实际模型识别，并通过分析美国生猪数据的5个序列演示迭代建模过程。
This article provides an expository account of the multivariate autoregressive moving average models and proposes an extended sample cross-correlation approach for practical model identification. An iterative model building procedure for applying these models to real data is discussed and demonstrated by analyzing the 5-series U.S. Hog Data.