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Threshold Vector Arma Models

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  • Marcella Niglio
  • Cosimo Damiano Vitale

Abstract

In this article, we propose the threshold vector autoregressive moving average model (TVARMA). It is a multivariate nonlinear time series model characterized by two or more regimes that follow a vector ARMA structure and where the switching among them is regulated by a latent variable. The TVARMA model represents a generalization of some nonlinear models proposed in the literature and shows interesting features that are explored. The condition for the strong and weak stationarity of the TVARMA model are presented and the moments up to order two of the process are derived.

Suggested Citation

  • Marcella Niglio & Cosimo Damiano Vitale, 2015. "Threshold Vector Arma Models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(14), pages 2911-2923, July.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:14:p:2911-2923
    DOI: 10.1080/03610926.2013.814785
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    Cited by:

    1. Muhammad Jaffri Mohd Nasir & Ramzan Nazim Khan & Gopalan Nair & Darfiana Nur, 2024. "Active-set based block coordinate descent algorithm in group LASSO for self-exciting threshold autoregressive model," Statistical Papers, Springer, vol. 65(5), pages 2973-3006, July.

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