A Comparison of Tests of the Independence of Two Covariance-Stationary Time Series
推导并比较了检验两个协方差平稳时间序列独立性的几种方法的近似斜率，发现回归检验的近似斜率至少不低于基于单变量ARIMA模型残差的检验，且蒙特卡洛模拟支持这一结论。
Abstract The approximate slopes of several tests of the independence of two covariance stationary time series are derived and compared. It is shown that the approximate slopes of regression tests are at least as great as those based on the residuals of univariate ARIMA models, and that there are cases in which the former are arbitrarily great while the latter are arbitrarily small. These analytical findings are supported by a Monte Carlo study that shows that in samples of size 100 and 250 the asymptotic distribution theory under the null hypothesis is adequate for all tests, but under alternatives to the null hypothesis the rate of Type II error for the test based on ARIMA model residuals is often more than double that of the regression tests. Key Words: IndependenceTime seriesTestsApproximate slopesMonte Carlo