Add to ORKGAbstract: Selecting the threshold variable is a key step in building a generalized threshold autoregressive (TAR) model. This paper proposes a semi-parametric method for this purpose that is based on a single-index functional coecient model. The asymptotic distribution of the estimator is obtained. A simple algorithm is given and its convergence is proved. Some simulations are reported. Two data sets are analyzed, one of which gives strong statistical support for ratio-dependent predation in Ecology. Key words and phrases: Local linear smoother, nonlinear time series, single-index coecient models, threshold autoregressive (TAR) time series models. 1
The subject of time series analysis has drawn significant attentions in recent years, since it is of...
Threshold models have a wide variety of applications in economics. Direct applications include model...
Threshold models have a wide variety of applications in economics. Direct applications include model...
In this paper we fit non-linear models. We build Threshold Autoregressive (TAR) and Generalized Auto...
Abstract: In this paper we propose a new class of nonlinear time series models, the threshold variab...
In this paper we propose a new class of nonlinear time series models, the threshold variable driven ...
<div><p>The threshold autoregressive (TAR) model is a class of nonlinear time series models that hav...
ABSTRACT. Over recent years, several nonlinear time series models have been proposed in the literatu...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
The subject of time series analysis has drawn significant attentions in recent years, since it is of...
Threshold models have a wide variety of applications in economics. Direct applications include model...
Threshold models have a wide variety of applications in economics. Direct applications include model...
In this paper we fit non-linear models. We build Threshold Autoregressive (TAR) and Generalized Auto...
Abstract: In this paper we propose a new class of nonlinear time series models, the threshold variab...
In this paper we propose a new class of nonlinear time series models, the threshold variable driven ...
<div><p>The threshold autoregressive (TAR) model is a class of nonlinear time series models that hav...
ABSTRACT. Over recent years, several nonlinear time series models have been proposed in the literatu...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
The subject of time series analysis has drawn significant attentions in recent years, since it is of...
Threshold models have a wide variety of applications in economics. Direct applications include model...
Threshold models have a wide variety of applications in economics. Direct applications include model...