Add to ORKGRecent developments in nonlinear time series modelling are reviewed. Three main types of nonlinear models are discussed: Markov Switching, Threshold Autoregression and Smooth Transition Autoregression. Classical and Bayesian estimation techniques are described for each model. Parametric tests for nonlinearity are reviewed with examples from the three types of models. Finally, forecasting and impulse response analysis is developed.Time-series analysis
In this paper we propose a new class of nonlinear time series models, the threshold variable driven ...
International audienceInterest is growing in methods for predicting and detecting regime shifts—chan...
International audienceInterest is growing in methods for predicting and detecting regime shifts—chan...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
Most of the recent work in time series analysis has been done on the assumption that the structure o...
The thesis is dedicated to study of nonlinear parametric models for financial time series. It contai...
The thesis is dedicated to study of nonlinear parametric models for financial time series. It contai...
textabstractThis paper surveys recent developments related to the smooth transition autoregressive [...
This paper considers the Bayesian analysis of threshold regression models. It shows that this analys...
Nonlinear time series models have been used extensively in recent years to model complex dynamics th...
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 ...
International audienceInterest is growing in methods for predicting and detecting regime shifts—chan...
International audienceInterest is growing in methods for predicting and detecting regime shifts—chan...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
The aim of the paper is to examine some of the key issues in nonlinear time series analysis. Tools a...
Most of the recent work in time series analysis has been done on the assumption that the structure o...
The thesis is dedicated to study of nonlinear parametric models for financial time series. It contai...
The thesis is dedicated to study of nonlinear parametric models for financial time series. It contai...
textabstractThis paper surveys recent developments related to the smooth transition autoregressive [...
This paper considers the Bayesian analysis of threshold regression models. It shows that this analys...
Nonlinear time series models have been used extensively in recent years to model complex dynamics th...
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 ...
International audienceInterest is growing in methods for predicting and detecting regime shifts—chan...
International audienceInterest is growing in methods for predicting and detecting regime shifts—chan...