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tsDyn (version 0.9-1)

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

5,189

Version

0.9-1

License

GPL (>= 2)

Maintainer

Antonio Fabio Di Narzo

Last Published

November 8th, 2012

Functions in tsDyn (0.9-1)

isLinear

isLinear
nlarDialog

GUI to nlar
tsDyn-package

Getting started with the tsDyn package
autotriples

Trivariate time series plots
autopairs

Bivariate time series plots
oneStep

oneStep
mse

Mean Square Error
selectHyperParms

Automatic selection of model hyper-parameters
autotriples.rgl

Interactive trivariate time series plots
nlar methods

nlar methods
TVAR.sim

Simulation of a multivariate Threshold Autoregressive model (TVAR)
irf

Impulse response function
LSTAR

Logistic Smooth Transition AutoRegressive model
MakeThSpec

Specification of the threshold search
VARrep

VAR representation
logLik.VECM

Extract Log-Likelihood
TVECM

Threshold Vector Error Correction model (VECM)
barry

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

extension of the bootstrap replications
STAR

STAR model
getTh

Extract threshold(s) coefficient
toLatex.setar

Latex representation of fitted setar models
regime

Extract variable showing regime
llar

Locally linear model
resVar

Residual variance
fevd

Forecast Error Variance Decomposition
predict

Predict method for objects of class nlar, VAR or VECM
lags.select

Selection of the lag with Information criterion.
nlar

Non-linear time series model, base class definition
BBCTest

Test of unit root against SETAR alternative
selectSETAR

Automatic selection of SETAR hyper-parameters
rank.select

Selection of the cointegrating rank with Information criterion.
UsUnemp

US unemployment series used in Caner and Hansen (2001)
TVAR.LRtest

Test of linearity
delta.lin

delta test of linearity
TVECM.HStest

Test of linear cointegration vs threshold cointegration
AAR

Additive nonlinear autoregressive model
fitted

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

US monthly industrial production from Hansen (1999)
LINEAR

Linear AutoRegressive models
TVAR.boot

Bootstrap a multivariate Threshold Autoregressive (TVAR) model
plot methods

Plotting methods for SETAR and LSTAR subclasses
setarTest

Test of linearity
nlar.struct

NLAR common structure
sigmoid

sigmoid functions
TVECM.sim

Simulation and bootstrap of bivariate VECM/TVECM
MAPE

Mean Absolute Percent Error
lineVar

Multivariate linear models: VAR and VECM
TVECM.SeoTest

No cointegration vs threshold cointegration test
computeGradient

computeGradient
SETAR

Self Threshold Autoregressive model
TVAR

Multivariate Threshold Autoregressive model
KapShinTest

Test of unit root against SETAR alternative with
delta

delta test of conditional independence
setar.sim

Simulation and bootstrap of Threshold Autoregressive model
VECM

Estimation of Vector error correction model (VECM)
VECM_symbolic

Virtua VECM model
rank.test

Test of the cointegrating rank
availableModels

Available models
logLik.nlVar

Extract Log-Likelihood
addRegime

addRegime test
predict_rolling

Rolling forecasts
NNET

Neural Network nonlinear autoregressive model
zeroyld

zeroyld time series