Ergodicity conditions for a double mixed Poisson autoregression

Abdelhakim Aknouche, Nacer Demmouche

Research output: Contribution to journalJournal articlepeer-review

1 Scopus citations


We propose a double mixed Poisson autoregression in which the intensity, scaled by a unit mean independent and identically distributed (i.i.d.) mixing process, has different regime specifications according to the state of a finite unobserved i.i.d. chain. Under some contraction in mean conditions, we show that the proposed model is strictly stationary and ergodic with a finite mean. Applications to various count time series models are given.

Original languageEnglish
Pages (from-to)6-11
Number of pages6
JournalStatistics and Probability Letters
StatePublished - Apr 2019


  • Contraction in mean
  • Double mixed Poisson autoregression
  • Ergodicity
  • Markov Switching INGARCH
  • Negative binomial mixture INGARCH
  • Weak dependence


Dive into the research topics of 'Ergodicity conditions for a double mixed Poisson autoregression'. Together they form a unique fingerprint.

Cite this