Sample Moments and Weak Convergence to Multivariate Stochastic Power Integrals
研究了含I(1)回归元的线性与非线性多元系统中最小二乘、最小绝对离差和极值估计量的样本矩，证明其弱收敛于多元随机幂积分，是单变量结果的多元推广。
This work considers sample moments arising from least squares, least absolute deviation, and extremum estimators of linear and nonlinear multivariate systems with I(1) regressors. The sample moments are shown to converge weakly to multivariate stochastic power integrals, and these results can be considered as a multivariate generalization of the univariate results reported earlier.