tsDyn: 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).

Version: 0.9-33
Imports: mnormt, mgcv, nnet, tseriesChaos, tseries, utils, vars, urca, forecast, MASS, Matrix, foreach
Suggests: sm, scatterplot3d, rgl, FinTS
Published: 2014-03-29
Author: Antonio Fabio Di Narzo [aut, cre], Jose Luis Aznarte [ctb], Matthieu Stigler [aut, cre]
Maintainer: Matthieu Stigler <Matthieu.Stigler at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://tsdyn.googlecode.com
NeedsCompilation: yes
Citation: tsDyn citation info
Materials: ChangeLog
In views: TimeSeries
CRAN checks: tsDyn results

Downloads:

Reference manual: tsDyn.pdf
Vignettes: Threshold cointegration: overview and implementation in R
tsDyn: Nonlinear autoregressive time series models in R
Package source: tsDyn_0.9-33.tar.gz
OS X binary: tsDyn_0.9-33.tgz
Windows binary: tsDyn_0.9-33.zip
Old sources: tsDyn archive

Reverse dependencies:

Reverse suggests: mFilter