tsDyn11.0.4.1 package

Nonlinear Time Series Models with Regime Switching

Additive nonlinear autoregressive model

Forecasting accuracy measures.

addRegime test

Long-term mean of an AR(p) process

Bivariate time series plots

Trivariate time series plots

Interactive trivariate time series plots

Available models

Test of unit root against SETAR alternative

Characteristic roots of the AR coefficients

Extract cointegration parameters A, B and PI

computeGradient

US unemployment series used in Caner and Hansen (2001)

delta test of linearity

delta test of conditional independence

Forecast Error Variance Decomposition

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

Extract threshold(s) coefficient

Generalized Impulse response Function (GIRF)

Impulse response function

isLinear

Test of unit root against SETAR alternative with

Selection of the lag with Information criterion.

Linear AutoRegressive models

Multivariate linear models: VAR and VECM

Locally linear model

Extract Log-Likelihood

Logistic Smooth Transition AutoRegressive model

Specification of the threshold search

Mean Absolute Percent Error

Mean Square Error

NLAR methods

Non-linear time series model, base class definition

NLAR common structure

Neural Network nonlinear autoregressive model

oneStep

Plotting methods for SETAR and LSTAR subclasses

Plot the Error Correct Term (ECT) response

Predict method for objects of class ‘nlar’ .

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

Rolling forecasts

Selection of the cointegrating rank with Information criterion.

Test of the cointegrating rank

Objects exported from other packages

Extract a variable showing the regime

Resampling schemes

Residual variance

Automatic selection of model hyper-parameters

Automatic selection of SETAR hyper-parameters

Self Threshold Autoregressive model

Simulation and bootstrap of Threshold Autoregressive model (SETAR)

Test of linearity against threshold (SETAR)

sigmoid functions

STAR model

Latex representation of fitted setar models

Getting started with the tsDyn package

Test of linearity

Multivariate Threshold Vector Autoregressive model

Simulation of a multivariate Threshold Autoregressive model (TVAR)

Test of linear cointegration vs threshold cointegration

Threshold Vector Error Correction model (VECM)

No cointegration vs threshold cointegration test

Simulation and bootstrap a VECM or bivariate TVECM

Simulate or bootstrap a VAR model

VAR representation

Estimation of Vector error correction model (VECM)

Virtual VECM model

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).

Maintainer: Matthieu Stigler License: GPL (>= 2) Last published: 2024-02-01

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