Open Access
2016 Stability and asymptotics for autoregressive processes
Likai Chen, Wei Biao Wu
Electron. J. Statist. 10(2): 3723-3751 (2016). DOI: 10.1214/16-EJS1213

Abstract

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.

Citation

Download Citation

Likai Chen. Wei Biao Wu. "Stability and asymptotics for autoregressive processes." Electron. J. Statist. 10 (2) 3723 - 3751, 2016. https://doi.org/10.1214/16-EJS1213

Information

Received: 1 July 2016; Published: 2016
First available in Project Euclid: 6 December 2016

zbMATH: 1353.62093
MathSciNet: MR3579674
Digital Object Identifier: 10.1214/16-EJS1213

Subjects:
Primary: 62E20 , 62M10

Keywords: autoregressive models , functional dependence measure , invariance principle , Markov process , nonlinear time series , stationarity

Rights: Copyright © 2016 The Institute of Mathematical Statistics and the Bernoulli Society

Vol.10 • No. 2 • 2016
Back to Top