Add to ORKGIn the application of autoregressive models the order of the model is often estimated using either a sequence of likelihood ratio tests or a likelihood based information criterion. The consistency of such procedures has been discussed extensively under the assumption that the characteristic roots of the autoregression are stationary. It is shown that these methods can be used regardless of the assumption to the characteristic roots
Graduation date: 1980Finite order autoregressive models for time series are often\ud used for predic...
The purpose of this paper is to compare different autoregressive models performance in case of incor...
In the presented work vector autoregression (VAR) models of finite order are examined. The main part...
AbstractTo determine the order of an autoregressive model, a new method based on information theoret...
To determine the order of an autoregressive model, a new method based on information theoretic crite...
We show that the order of integration of a vector autoregressive process is equal to the difference ...
This correspondence addresses the problem of order determination of autoregressive models by Bayesia...
This correspondence addresses the problem of order determination of autoregressive models by Bayesia...
This correspondence addresses the problem of order determination of autoregressive models by Bayesia...
Vector time series analysis takes the same model order and model type for the different signals invo...
In this paper we propose a new identification method based on the residual white noise autoregressiv...
Vector time series analysis takes the same model order and model type for the different signals invo...
Abstract. The classical theory of rank-based inference is essentially limited to univariate linear m...
This paper examines the problem of order selection in connection to the forecasting performance for ...
Abstract—In vector autoregressive modeling, the order selected with the Akaike Information Criterion...
Graduation date: 1980Finite order autoregressive models for time series are often\ud used for predic...
The purpose of this paper is to compare different autoregressive models performance in case of incor...
In the presented work vector autoregression (VAR) models of finite order are examined. The main part...
AbstractTo determine the order of an autoregressive model, a new method based on information theoret...
To determine the order of an autoregressive model, a new method based on information theoretic crite...
We show that the order of integration of a vector autoregressive process is equal to the difference ...
This correspondence addresses the problem of order determination of autoregressive models by Bayesia...
This correspondence addresses the problem of order determination of autoregressive models by Bayesia...
This correspondence addresses the problem of order determination of autoregressive models by Bayesia...
Vector time series analysis takes the same model order and model type for the different signals invo...
In this paper we propose a new identification method based on the residual white noise autoregressiv...
Vector time series analysis takes the same model order and model type for the different signals invo...
Abstract. The classical theory of rank-based inference is essentially limited to univariate linear m...
This paper examines the problem of order selection in connection to the forecasting performance for ...
Abstract—In vector autoregressive modeling, the order selected with the Akaike Information Criterion...
Graduation date: 1980Finite order autoregressive models for time series are often\ud used for predic...
The purpose of this paper is to compare different autoregressive models performance in case of incor...
In the presented work vector autoregression (VAR) models of finite order are examined. The main part...