We develop Bayesian methods of analysis for a new class of threshold autoregressive models: endogenous delay threshold. We apply our methods to the commonly used sunspot data set and find strong evidence in favor of the Endogenous Delay Threshold Autoregressive (EDTAR) model over linear and traditional threshold autoregressions
In this paper, we develop a Bayesian analysis of a threshold antoregressive model with exponential n...
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...
Threshold Autoregression is a powerful statistical tool for modeling structural nonlinear relationsh...
This paper considers the Bayesian analysis of threshold regression models. It shows that this analys...
A Bayesian approach in threshold moving average model for time series with two regimes is provided. ...
We discuss a general approach to dynamic sparsity modeling in multivariate time series analysis. Tim...
An approach to Bayesian model selection in self-exciting threshold autoregressive (SETAR) models is ...
The subject of time series analysis has drawn significant attentions in recent years, since it is of...
This thesis is mainly concerned with the estimation of parameters of a first-order Smooth Threshold ...
Abstract. An approach to Bayesian model selection in self-exciting threshold autoregressive (SETAR) ...
We consider Bayesian analysis of threshold autoregressive moving average model with exogenous inputs...
Bayesian estimation and one-step-ahead forecasting for two-regime TAR model, as well as moni-toring ...
In this paper we fit non-linear models. We build Threshold Autoregressive (TAR) and Generalized Auto...
Wavelets are applied to identify the time delay and thresholds in open-loop threshold autoregressive...
In this paper, we develop a Bayesian analysis of a threshold antoregressive model with exponential n...
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...
Threshold Autoregression is a powerful statistical tool for modeling structural nonlinear relationsh...
This paper considers the Bayesian analysis of threshold regression models. It shows that this analys...
A Bayesian approach in threshold moving average model for time series with two regimes is provided. ...
We discuss a general approach to dynamic sparsity modeling in multivariate time series analysis. Tim...
An approach to Bayesian model selection in self-exciting threshold autoregressive (SETAR) models is ...
The subject of time series analysis has drawn significant attentions in recent years, since it is of...
This thesis is mainly concerned with the estimation of parameters of a first-order Smooth Threshold ...
Abstract. An approach to Bayesian model selection in self-exciting threshold autoregressive (SETAR) ...
We consider Bayesian analysis of threshold autoregressive moving average model with exogenous inputs...
Bayesian estimation and one-step-ahead forecasting for two-regime TAR model, as well as moni-toring ...
In this paper we fit non-linear models. We build Threshold Autoregressive (TAR) and Generalized Auto...
Wavelets are applied to identify the time delay and thresholds in open-loop threshold autoregressive...
In this paper, we develop a Bayesian analysis of a threshold antoregressive model with exponential n...
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...
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