A general dependence test and applications
提出一种基于相关积分的独立性检验，适用于序列相关数据，蒙特卡洛模拟显示其检验效力接近或优于BDS检验，并应用于美国失业率模型。
We describe a test, based on the correlation integral, for the independence of a variable and a vector that can be used with serially dependent data. Monte Carlo simulations suggest that the test has good power to detect dependence in several models, performing nearly as well or better than the BDS test in univariate time series and complementing the BDS test in distributed lag models. Finally, we apply our test in conjunction with the BDS test to examine models of US unemployment rates. © 1998 John Wiley & Sons, Ltd.