Seemingly Unrelated Time Series Equations and a Test for Homogeneity
构建了一个包含趋势和季节成分的多元结构时间序列模型，提出同质性系统（观测值的任意线性组合遵循相同时间序列过程）对应扰动协方差矩阵成比例的模型，并开发了频域同质性得分检验，通过蒙特卡洛实验评估其有限样本性质，还描述了用于同质性系统的序列相关检验。
A multivariate structural time series model made up of unobserved components such as trends and seasonals is formulated. A homogeneous system, in which any linear combination of the observations follows the same time series process, is shown to correspond to a multivariate structural model in which the covariance matrices of the disturbances are proportional. A homogeneous model is considerably easier to estimate than the more general model and a score test of homogeneity can be constructed in the frequency domain. The finite-sample properties of this test are evaluated in a series of Monte Carlo experiments. Finally, a test of serial correlation for use in homogeneous systems is described.