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 datagenerating mechanisms. Our stability result allows both short- and longrange dependence. With functional dependence measures, we can establish an asymptotic theory for the underlying processes.
| Original language | English |
|---|---|
| Article number | A65 |
| Pages (from-to) | 3723-3751 |
| Number of pages | 29 |
| Journal | Electronic Journal of Statistics |
| Volume | 10 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2016 |
Keywords
- Autoregressive models
- Functional dependence measure
- Invariance principle
- Markov process
- Nonlinear time series
- Stationarity