Article ID: | iaor200969454 |
Country: | United Kingdom |
Volume: | 28 |
Issue: | 3 |
Start Page Number: | 266 |
End Page Number: | 276 |
Publication Date: | Apr 2009 |
Journal: | Journal of Forecasting |
Authors: | Petruccelli Joseph D, Onofrei Alina, Wilbur Jayson D |
Keywords: | cusum charts |
As a part of an effective self-exciting threshold autoregressive (SETAR) modeling methodology, it is important to identify processes exhibiting SETAR-type nonlinearity. A number of tests of nonlinearity have been developed in the literature. However, it has recently been shown that all these tests perform poorly for SETAR-type nonlinearity detection in the presence of additive outliers. In this paper, we develop an improved test for SETAR-type nonlinearity in time series. The test is an outlier-robust test based on the cumulative sums of ordered weighted residuals from generalized maximum likelihood fits. A Monte Carlo study confirms that the proposed test is competitive with existing tests for data from uncontaminated SETAR models and superior to them for SETAR data contaminated with additive outliers.