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Nonlinear time series models with regime switching
Antonio Fabio Di Narzo [aut, cre], Jose Luis Aznarte [ctb], Matthieu Stigler [aut, cre]
GPL (>= 2)
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).
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tsDyn 0.9-32 3 years 1 week ago
tsDyn 0.9-2 3 years 30 weeks ago
tsDyn 0.9-1 3 years 37 weeks ago
tsDyn 0.9-0 3 years 38 weeks ago
tsDyn 0.8-1 4 years 22 weeks ago
tsDyn 0.7-62 4 years 31 weeks ago
tsDyn 0.7-60 5 years 10 weeks ago
tsDyn 0.7-52 5 years 11 weeks ago
tsDyn 0.7-40 5 years 49 weeks ago
tsDyn 0.7-30 6 years 3 weeks ago
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