Stability and asymptotics for autoregressive processes

  • Likai Chen
  • , Wei Biao Wu

    Research output: Contribution to journalArticlepeer-review

    5 Scopus citations

    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 languageEnglish
    Article numberA65
    Pages (from-to)3723-3751
    Number of pages29
    JournalElectronic Journal of Statistics
    Volume10
    Issue number2
    DOIs
    StatePublished - 2016

    Keywords

    • Autoregressive models
    • Functional dependence measure
    • Invariance principle
    • Markov process
    • Nonlinear time series
    • Stationarity

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