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tsDyn

Package tsDyn implements a variety of non-linear time series models. To read more about it, look at:

the wiki
the FAQ

Installation

You can install the released version of tsDyn from CRAN with:

install.packages("tsDyn")

Development version

Most of the development is hosted under the branch called Dev94. To install that version, use:

library(remotes)
remotes::install_github("MatthieuStigler/tsDyn/tsDyn", ref = "dev")

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Version

Install

install.packages('tsDyn')

Monthly Downloads

4,965

Version

11.0.2

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Repository

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

Maintainer

Matthieu Stigler

Last Published

March 9th, 2022

Functions in tsDyn (11.0.2)

Test of unit root against SETAR alternative

Multivariate Threshold Vector Autoregressive model

Specification of the threshold search

Test of unit root against SETAR alternative with

Generalized Impulse response Function (GIRF)

Mean Absolute Percent Error

US monthly industrial production from Hansen (1999)

US unemployment series used in Caner and Hansen (2001)

Test of linearity

Simulation of a multivariate Threshold Autoregressive model (TVAR)

Simulate or bootstrap a VAR model

Characteristic roots of the AR coefficients

Virtual VECM model

Estimation of Vector error correction model (VECM)

Forecasting accuracy measures.

Additive nonlinear autoregressive model

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

Mean Square Error

Extract threshold(s) coefficient

Test of linear cointegration vs threshold cointegration

Test of the cointegrating rank

Long-term mean of an AR(p) process

Non-linear time series model, base class definition

Selection of the lag with Information criterion.

NLAR common structure

Objects exported from other packages

Trivariate time series plots

Threshold Vector Error Correction model (VECM)

No cointegration vs threshold cointegration test

Bivariate time series plots

VAR representation

Latex representation of fitted setar models

Impulse response function

autotriples.rgl

Interactive trivariate time series plots

Extract cointegration parameters A, B and PI

computeGradient

computeGradient

availableModels

Available models

Simulation and bootstrap a VECM or bivariate TVECM

Forecast Error Variance Decomposition

delta test of conditional independence

Predict method for objects of class ‘nlar’.

sigmoid functions

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

Extract a variable showing the regime

Locally linear model

Residual variance

setarTest_IIPUs_results

Results from the setarTest, applied on Hansen (1999) data

Simulation and bootstrap of Threshold Autoregressive model (SETAR)

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

Extract Log-Likelihood

Test of linearity against threshold (SETAR)

Automatic selection of SETAR hyper-parameters

Neural Network nonlinear autoregressive model

predict_rolling

Rolling forecasts

Self Threshold Autoregressive model

Selection of the cointegrating rank with Information criterion.

delta test of linearity

Logistic Smooth Transition AutoRegressive model

Monthly US unemployment

Multivariate linear models: VAR and VECM

Plotting methods for SETAR and LSTAR subclasses

Plot the Error Correct Term (ECT) response

Linear AutoRegressive models

Getting started with the tsDyn package

zeroyld time series

Resampling schemes

selectHyperParms

Automatic selection of model hyper-parameters