Add to ORKGDescription Implements nonlinear autoregressive (AR) time series models. For univariate se-ries, a non-parametric approach is available through additive nonlinear AR. Parametric model-ing and testing for regime switching dynamics is available when the transition is either di-rect (TAR: threshold AR) or smooth (STAR: smooth transition AR, LSTAR). For multivariate se-ries, one can estimate a range of TVAR or threshold cointegration TVECM mod-els with two or three regimes. Tests can be con-ducted for TVAR as well as for TVECM (Hansen and Seo 2002 and Seo 2006). License GPL (> = 2
In this paper we propose the threshold vector autoregressive moving average model (TVARMA). It is a ...
In this paper we propose a method for determining the number of regimes in threshold autoregressive ...
We generalise the mixture autoregressive, MAR, model to the logistic mixture autoregressive with exo...
Although linear autoregressive models are useful to practitioners in different fields, often a nonli...
In this paper we propose a new class of nonlinear time series models, the threshold variable driven ...
Abstract: In this paper we propose a new class of nonlinear time series models, the threshold variab...
textabstractThis paper surveys recent developments related to the smooth transition autoregressive [...
Although linear autoregressive models are useful to practitioners in different fields, often a nonl...
Recent developments in nonlinear time series modelling are reviewed. Three main types of nonlinear m...
This paper introduces a variant of the smooth transition autoregression (STAR).Theproposedmodelisabl...
International audienceInterest is growing in methods for predicting and detecting regime shifts—chan...
Abstract: One of the most important family of nonlinear time-series models, capable of exhibiting li...
Nonlinear nonstationary models for time series are considered, where the series is generated from an...
This paper introduces new LM specification procedures to choose between Logistic and Exponential Smo...
This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MST...
In this paper we propose the threshold vector autoregressive moving average model (TVARMA). It is a ...
In this paper we propose a method for determining the number of regimes in threshold autoregressive ...
We generalise the mixture autoregressive, MAR, model to the logistic mixture autoregressive with exo...
Although linear autoregressive models are useful to practitioners in different fields, often a nonli...
In this paper we propose a new class of nonlinear time series models, the threshold variable driven ...
Abstract: In this paper we propose a new class of nonlinear time series models, the threshold variab...
textabstractThis paper surveys recent developments related to the smooth transition autoregressive [...
Although linear autoregressive models are useful to practitioners in different fields, often a nonl...
Recent developments in nonlinear time series modelling are reviewed. Three main types of nonlinear m...
This paper introduces a variant of the smooth transition autoregression (STAR).Theproposedmodelisabl...
International audienceInterest is growing in methods for predicting and detecting regime shifts—chan...
Abstract: One of the most important family of nonlinear time-series models, capable of exhibiting li...
Nonlinear nonstationary models for time series are considered, where the series is generated from an...
This paper introduces new LM specification procedures to choose between Logistic and Exponential Smo...
This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MST...
In this paper we propose the threshold vector autoregressive moving average model (TVARMA). It is a ...
In this paper we propose a method for determining the number of regimes in threshold autoregressive ...
We generalise the mixture autoregressive, MAR, model to the logistic mixture autoregressive with exo...