We prove mixing convergence of least squares estimator of autoregressive parameters for supercritical Gaussian autoregressive processes of order 2 having real characteristic roots with different absolute values. We use an appropriate random scaling such that the limit distribution is a two-dimensional normal distribution concentrated on a one-dimensional ray determined by the characteristic root having the larger absolute value.

翻译：我们证明,对超临界高斯自动递减进程2的自动递减参数的最小正方数估计值的混合结合具有不同绝对值的真正特性根部。 我们使用一个适当的随机比例,使极限分布是一个二维正常分布,集中在由具有较大绝对值的特性根决定的一维射线上。