Bootstrap order selection for SETAR models
Date
2015Author
Fenga, L.Politis, Dimitris Nicolas
Source
Journal of Statistical Computation and SimulationVolume
85Issue
2Pages
235-250Google Scholar check
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In this paper, we investigate the selecting performances of a bootstrapped version of the Akaike information criterion for nonlinear self-exciting threshold autoregressive-type data generating processes. Empirical results will be obtained via Monte Carlo simulations. The quality of our method is assessed by comparison with its non-bootstrap counterpart and through a novel procedure based on artificial neural networks. © 2013, © 2013 Taylor & Francis.