On the Identifiability Conditions in Some Nonlinear Time Series Models

Jungsik Noh; Sangyeol Lee

doi:10.57805/revstat.v14i4.195

On the Identifiability Conditions in Some Nonlinear Time Series Models

Authors

Jungsik Noh University of Texas Southwestern Medical Center
Sangyeol Lee Seoul National University

DOI:

https://doi.org/10.57805/revstat.v14i4.195

Keywords:

identifiability, nonlinear time series models, GARCH-type models, smooth transition GARCH models, Poisson autoregressive models, smooth transition autoregressive models

Abstract

In this study, we consider the identifiability problem for nonlinear time series models. Special attention is paid to smooth transition GARCH, nonlinear Poisson autoregressive, and multiple regime smooth transition autoregressive models. Some sufficient conditions are obtained to establish the identifiability of these models.

Downloads

REVSTAT2016v14n4_2

Published

2016-10-21

How to Cite

Noh , J., & Lee , S. (2016). On the Identifiability Conditions in Some Nonlinear Time Series Models. REVSTAT-Statistical Journal, 14(4), 395–413. https://doi.org/10.57805/revstat.v14i4.195