The Identification of Thresholds and Time Delay in Self-Exciting Threshold AR Model by Wavelet

TL;DR

This paper introduces a wavelet-based method for identifying thresholds and time delays in self-exciting threshold autoregressive models, extending previous approaches to more general cases without delay constraints.

Contribution

It develops an empirical wavelet approach to accurately identify thresholds and delays in SETAR models without restrictions on delay size.

Findings

Successfully identified thresholds and delays in simulated data

Extended the applicability of wavelet methods to general SETAR models

Improved accuracy over existing methods in threshold detection

Abstract

In this paper we studied about the wavelet identification of the thresholds and time delay for more general case without the constraint that the time delay is smaller than the order of the model. Here we composed an empirical wavelet from the SETAR (Self-Exciting Threshold Autoregressive) model and identified the thresholds and time delay in the model using it.