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连接两条时间序列的动态回归与分布滞后模型识别AI 解读

A methodology is introduced for identifying dynamic regression or distributed lag models relating two time series. First, specification of a bivariate time-series model is discussed, and its relationship to the usual dynamic regression model is indicated. Then, a two-stage identification procedure is presented which involves fitting univariate time-series models to each series, and identifying a dynamic shock model relating the two univariate model innovation series. The…

检验两个协方差平稳时间序列的独立性：单变量残差互相关方法AI 解读

A two-stage method is proposed for investigating the independence of two covariance-stationary time series. It involves, first, fitting univariate models to each of the series, and then cross-correlating the two residual series thereby obtained. The asymptotic distribution of such a set of lagged residual cross-correlations is established to be of a very simple form under the null hypothesis of the two series' independence. A Monte Carlo study verifies the applicability of…