Stability and asymptotics for autoregressive processes

被引:3
作者
Chen, Likai [1 ]
Wu, Wei Biao [1 ]
机构
[1] Univ Chicago, Dept Stat, Chicago, IL 60637 USA
基金
美国国家科学基金会;
关键词
Autoregressive models; Markov process; non-linear time series; stationarity; functional dependence measure; invariance principle; CENTRAL LIMIT-THEOREMS; APPROXIMATION; SUMS; GARCH;
D O I
10.1214/16-EJS1213
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The paper studies infinite order autoregressive models for both temporal and spatial processes. We present sufficient conditions for the existence of stationary distributions. To understand the underlying dynamics and to capture the dependence structure, we introduce functional dependence measures and relate them with Lipschitz coefficients of the data-generating mechanisms. Our stability result allows both short-and long-range dependence. With functional dependence measures, we can establish an asymptotic theory for the underlying processes.
引用
收藏
页码:3723 / 3751
页数:29
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