CRAN/E | tsDyn

tsDyn

Nonlinear Time Series Models with Regime Switching

Installation

About

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).

Citation tsDyn citation info
github.com/MatthieuStigler/tsDyn/wiki
Bug report File report

Key Metrics

Version 11.0.4.1
R ≥ 3.5.0
Published 2024-02-01 85 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks tsDyn results

Downloads

Yesterday 99 0%
Last 7 days 631 -31%
Last 30 days 3.755 -29%
Last 90 days 12.229 +19%
Last 365 days 42.381 -1%

Maintainer

Maintainer

Matthieu Stigler

Matthieu.Stigler@gmail.com

Authors

Antonio Fabio Di Narzo

aut

Jose Luis Aznarte

ctb

Matthieu Stigler

aut / cre

Material

README
NEWS
Reference manual
Package source

In Views

Econometrics
Finance
TimeSeries

Vignettes

Threshold cointegration: overview and implementation in R
tsDyn: Nonlinear autoregressive time series models in R

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

tsDyn archive

Depends

R ≥ 3.5.0

Imports

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

Suggests

sm
scatterplot3d
rgl
tidyverse
rugarch

Reverse Depends

dvqcc

Reverse Imports

GVARX
NonlinearTSA

Reverse Suggests

mFilter
svars