Analysis and Generalisation of a Multivariate Exponential Smoothing Model
分析了Enns等人的多元指数平滑模型，发现其结构可简化为单变量模型进行估计和预测，并进一步推广到包含多项式趋势和季节因素的更一般单变量模型及其多元推广。
The multivariate exponential smoothing model of Enns, Machak, Spivey and Wrobleski is examined and it is found that its structure is such that it can be estimated by using techniques designed for a univariate exponential smoothing model. Similarly forecasts can be made using algorithms for the univariate model. The model can therefore be handled very easily. A more general univariate time series model, which can include polynomial trends and seasonal factors, is then set up and a multivariate generalisation, analogous to the multivariate exponential smoothing model, is introduced. It is shown that this model can also be handled using algorithms designed for the univariate case.