This paper proposes a linear approximation of the nonlinear Threshold AutoRegressive model. It is shown that there is a relation between the autoregressive order of the threshold model and the order of its autoregressive moving average approximation. The main advantage of this approximation can be found in the extension of some theoretical results developed in the linear setting to the nonlinear domain. Among them is proposed a new order estimation procedure for threshold models whose performance is compared, through a Monte Carlo study, to other criteria largely employed in the nonlinear threshold context.
Linear approximation of the Threshold AutoRegressive model: an application to order estimation
Francesco Giordano;Marcella Niglio
;Cosimo Damiano Vitale
2022-01-01
Abstract
This paper proposes a linear approximation of the nonlinear Threshold AutoRegressive model. It is shown that there is a relation between the autoregressive order of the threshold model and the order of its autoregressive moving average approximation. The main advantage of this approximation can be found in the extension of some theoretical results developed in the linear setting to the nonlinear domain. Among them is proposed a new order estimation procedure for threshold models whose performance is compared, through a Monte Carlo study, to other criteria largely employed in the nonlinear threshold context.File in questo prodotto:
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