In this article, we introduce an automatic identi\ufb01cation procedure for transfer function models. These models are commonplace in time-series analysis, but their identi\ufb01cation can be complex. To tackle this problem, we propose to couple a nonlinear conditional least-squares algorithm with a genetic search over the model space. We illustrate the performances of our proposal by examples on simulated and real data
This paper develops a genetic algorithm based technique that may be used to identify multivariable s...
The last ten years has seen the introduction and rapid growth of a market in weather derivatives, fi...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...
In this article, we introduce an automatic identification procedure for transfer function models. T...
We present a model and a computational procedure for dealing with seasonality and regime changes in ...
Many nonstationary time series exhibit changes in the trend and seasonality structure, that may be ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
This paper proposes an extension of Periodic AutoRegressive (PAR) modelling for time series with evo...
The paper presents an algorithm for computing the asymptotic Fisher information matrix of a possibly...
Many time series exhibits both nonlinearity and nonstationarity. Though both features have been ofte...
One of the most powerful and widely used methodologies for forecasting economic time series is the c...
The popular 'airline' model for a seasonal time series assumes that a variable needsdouble differenc...
This paper develops a genetic algorithm based technique that may be used to identify multivariable s...
The last ten years has seen the introduction and rapid growth of a market in weather derivatives, fi...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...
In this article, we introduce an automatic identification procedure for transfer function models. T...
We present a model and a computational procedure for dealing with seasonality and regime changes in ...
Many nonstationary time series exhibit changes in the trend and seasonality structure, that may be ...
A nonlinear version of the threshold autoregressive model for time series is introduced. A peculiar ...
This paper proposes an extension of Periodic AutoRegressive (PAR) modelling for time series with evo...
The paper presents an algorithm for computing the asymptotic Fisher information matrix of a possibly...
Many time series exhibits both nonlinearity and nonstationarity. Though both features have been ofte...
One of the most powerful and widely used methodologies for forecasting economic time series is the c...
The popular 'airline' model for a seasonal time series assumes that a variable needsdouble differenc...
This paper develops a genetic algorithm based technique that may be used to identify multivariable s...
The last ten years has seen the introduction and rapid growth of a market in weather derivatives, fi...
We present a method for investigating the evolution of trend and seasonality in an observed time ser...