Nonlinear Time Series Models with Regime Switching

Implements nonlinear autoregressive (AR) time series models. For univariate series, a non-parametric approach is available through additive nonlinear AR. Parametric modeling and testing for regime switching dynamics is available when the transition is either direct (TAR: threshold AR) or smooth (STAR: smooth transition AR, LSTAR). For multivariate series, one can estimate a range of TVAR or threshold cointegration TVECM models with two or three regimes. Tests can be conducted for TVAR as well as for TVECM (Hansen and Seo 2002 and Seo 2006).


Reference manual

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10-1.2 by Ho Tsung-wu, 2 years ago

Browse source code at

Authors: Antonio Fabio Di Narzo [aut] , Jose Luis Aznarte [ctb] , Matthieu Stigler [aut] , Ho Tsung-wu [cre]

Documentation:   PDF Manual  

Task views: Econometrics, Empirical Finance, Time Series Analysis

GPL (>= 2) license

Imports mnormt, mgcv, nnet, tseriesChaos, tseries, utils, vars, urca, forecast, MASS, Matrix, foreach, methods

Suggests sm, scatterplot3d, rgl

Imported by GVARX, NonlinearTSA.

Depended on by dvqcc.

Suggested by mFilter, svars.

See at CRAN