Break Detection for a Class of Nonlinear Time Series Models

. This article considers the problem of detecting break points for a nonstationary time series. Specifically, the time series is assumed to follow a parametric nonlinear time‐series model in which the parameters may change values at fixed times. In this formulation, the number and locations of the...

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Veröffentlicht in:	Journal of time series analysis 2008-09, Vol.29 (5), p.834-867
Hauptverfasser:	Davis, Richard A., Lee, Thomas C. M., Rodriguez-Yam, Gabriel A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Econometrics Generalized autoregressive conditionally heteroscedastic process genetic algorithm Genetic algorithms Mathematical analysis minimum description length principle model selection Model testing multiple change point Non-linear models non-stationary time series state-space models Statistical methods Stochastic models stochastic volatility model Structural change Studies Time series
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