We prove absolute regularity ($\beta$-mixing) for nonstationary and multivariate versions of two popular classes of integer-valued processes. We show how this result can be used to prove asymptotic normality of a least squares estimator of an involved model parameter.

翻译：我们证明了两种流行整数值过程类的非平稳、多元版本的绝对正则性（$\beta$-混合）。我们展示了如何利用这一结果来证明一个复杂模型参数的最小二乘估计量的渐近正态性。