Probabilistic properties of a nonlinear ARMA process with markov switching

Oesook Lee

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

We consider a nonlinear autoregressive moving average (ARMA) process with Markov switching and find sufficient conditions for strict stationarity, geometric ergodicity, and the existence of moments of the process with respect to the stationary distribution. Functional central limit theorem is also obtained.

Original languageEnglish
Pages (from-to)193-204
Number of pages12
JournalCommunications in Statistics - Theory and Methods
Volume34
Issue number1
DOIs
StatePublished - 2005

Keywords

  • Functional central limit theorem
  • Geometric ergodicity
  • Markov switching
  • Moment
  • Nonlinear ARMA(p, q) model
  • Stationarity

Fingerprint

Dive into the research topics of 'Probabilistic properties of a nonlinear ARMA process with markov switching'. Together they form a unique fingerprint.

Cite this