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tsDyn (version 0.9-44)

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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Install

install.packages('tsDyn')

Monthly Downloads

4,965

Version

0.9-44

License

GPL (>= 2)

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Repository

http://github.com/MatthieuStigler/tsDyn/wiki

Maintainer

Matthieu Stigler

Last Published

May 22nd, 2016

Functions in tsDyn (0.9-44)

US unemployment series used in Caner and Hansen (2001)

Test of linearity

Additive nonlinear autoregressive model

Bootstrap a multivariate Threshold Autoregressive (TVAR) model

Forecasting accuracy measures.

Test of linear cointegration vs threshold cointegration

predict_rolling

Rolling forecasts

Extract cointegration parameters A, B and PI

availableModels

Available models

Extract Log-Likelihood

zeroyld time series

VAR representation

sigmoid functions

Bootstrap a Vector Autoregressive (VAR) model

Forecast Error Variance Decomposition

Locally linear model

Simulation and bootstrap of bivariate VECM/TVECM

Test of the cointegrating rank

Selection of the lag with Information criterion.

computeGradient

computeGradient

Specification of the threshold search

Multivariate Threshold Autoregressive model

Impulse response function

Self Threshold Autoregressive model

NLAR common structure

Latex representation of fitted setar models

No cointegration vs threshold cointegration test

Getting started with the tsDyn package

US monthly industrial production from Hansen (1999)

Extract variable showing regime

Predict method for objects of class ‘nlar’.

selectHyperParms

Automatic selection of model hyper-parameters

extension of the bootstrap replications

Test of unit root against SETAR alternative

Simulation and bootstrap of Threshold Autoregressive model

delta test of linearity

Non-linear time series model, base class definition

Extract Log-Likelihood

Estimation of Vector error correction model (VECM)

Threshold Vector Error Correction model (VECM)

Extract threshold(s) coefficient

Trivariate time series plots

Test of unit root against SETAR alternative with

Automatic selection of SETAR hyper-parameters

Multivariate linear models: VAR and VECM

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

Selection of the cointegrating rank with Information criterion.

Virtua VECM model

Linear AutoRegressive models

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

Residual variance

Predict method for objects of class ‘VAR’ or ‘VECM’

Logistic Smooth Transition AutoRegressive model

Mean Absolute Percent Error

Plotting methods for SETAR and LSTAR subclasses

autotriples.rgl

Interactive trivariate time series plots

Mean Square Error

Simulation of a multivariate Threshold Autoregressive model (TVAR)

Bivariate time series plots

delta test of conditional independence

Test of linearity

Neural Network nonlinear autoregressive model