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tsDyn (version 0.9-0)

Nonlinear time series models with regime switching

Description

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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Version

Install

install.packages('tsDyn')

Monthly Downloads

4,965

Version

0.9-0

License

GPL (>= 2)

Maintainer

Antonio Fabio Di Narzo

Last Published

October 29th, 2012

Functions in tsDyn (0.9-0)

lags.select

Selection of the lag with Information criterion.
barry

Time series of PPI used as example in Bierens and Martins (2010)
LSTAR

Logistic Smooth Transition AutoRegressive model
logLik.VECM

Extract Log-Likelihood
UsUnemp

US unemployment series used in Caner and Hansen (2001)
VECM

Estimation of Vector error correction model (VECM)
TVECM.SeoTest

No cointegration vs threshold cointegration test
autotriples

Trivariate time series plots
isLinear

isLinear
predict

Predict method for objects of class nlar, VAR or VECM
TVAR

Multivariate Threshold Autoregressive model
TVAR.sim

Simulation of a multivariate Threshold Autoregressive model (TVAR)
plot methods

Plotting methods for SETAR and LSTAR subclasses
getTh

Extract threshold(s) coefficient
setar.sim

Simulation and bootstrap of Threshold Autoregressive model
fitted

fitted method for objects of class nlVar, i.e. VAR and VECM models.
setarTest

Test of linearity
addRegime

addRegime test
TVECM.sim

Simulation and bootstrap of bivariate VECM/TVECM
autotriples.rgl

Interactive trivariate time series plots
oneStep

oneStep
TVAR.LRtest

Test of linearity
fevd

Forecast Error Variance Decomposition
selectHyperParms

Automatic selection of model hyper-parameters
nlar

Non-linear time series model, base class definition
computeGradient

computeGradient
nlar.struct

NLAR common structure
nlarDialog

GUI to nlar
SETAR

Self Threshold Autoregressive model
predict_rolling

Rolling forecasts
delta

delta test of conditional independence
TVECM.HStest

Test of linear cointegration vs threshold cointegration
zeroyld

zeroyld time series
NNET

Neural Network nonlinear autoregressive model
TVECM

Threshold Vector Error Correction model (VECM)
MakeThSpec

Specification of the threshold search
mse

Mean Square Error
STAR

STAR model
KapShinTest

Test of unit root against SETAR alternative with
TVAR.boot

Bootstrap a multivariate Threshold Autoregressive (TVAR) model
rank.test

Test of the cointegrating rank
extendBoot

extension of the bootstrap replications
BBCTest

Test of unit root against SETAR alternative
llar

Locally linear model
regime

Extract variable showing regime
MAPE

Mean Absolute Percent Error
selectSETAR

Automatic selection of SETAR hyper-parameters
toLatex.setar

Latex representation of fitted setar models
VECM_symbolic

Virtua VECM model
AAR

Additive nonlinear autoregressive model
logLik.nlVar

Extract Log-Likelihood
tsDyn-package

Getting started with the tsDyn package
resVar

Residual variance
rank.select

Selection of the cointegrating rank with Information criterion.
sigmoid

sigmoid functions
nlar methods

nlar methods
availableModels

Available models
delta.lin

delta test of linearity
IIPUs

US monthly industrial production from Hansen (1999)
VARrep

VAR representation
autopairs

Bivariate time series plots
irf

Impulse response function
LINEAR

Linear AutoRegressive models
lineVar

Multivariate linear models: VAR and VECM