Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/60677
Title: Modeling nonlinear time series using improved least squares method
Authors: Nakamura, T
Small, M
Issue Date: 2006
Publisher: World Scientific
Source: International journal of bifurcation and chaos in applied sciences and engineering, 2006, v. 16, no. 2, p. 445-464 How to cite?
Journal: International journal of bifurcation and chaos in applied sciences and engineering 
Abstract: We improve the least squares (LS) method for building models of a nonlinear dynamical system given finite time series which are contaminated by observational noise. When the noise level is low. the LS method gives good estimates for the parameters, however. the models selected as the best by information criteria often tend to be over-parameterized or even degenerate. We observe that the correct model is riot selected as the best model despite belonging to the chosen model class. To overcome this, we propose a simple but very effective idea to use the LS method more appropriately. We apply the method for model selection. Numerical studies indicate that the method can be used to apply information criteria more effectively, and generally avoid over-fitting and model degeneracy.
URI: http://hdl.handle.net/10397/60677
ISSN: 0218-1274
EISSN: 1793-6551
DOI: 10.1142/S0218127406014927
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