The behavioural framework has several attractions to offer for the identification of multivariable systems. Some of the variables may be left unexplained without the need for a distinction between inputs and outputs; criteria for model quality are independent of the chosen parameterization; and...

This paper is concerned with linear dynamic factor models. In such models the observed process is decomposed into a structural part called the latent process, and a remainder that is called noise. The observed variables are treated in a symmetric way, so that no distinction between inputs and...

This paper is concerned with linear dynamic factor models. In such models the observed process is decomposed into a structural part called the latent process, and a remainder that is called noise. The observed variables are treated in a symmetric way, so that no distinction between inputs and...

This paper is concerned with linear dynamic factor models. In such models the observed process is decomposed into a structural part called the latent process, and a remainder that is called noise. The observed variables are treated in a symmetric way, so that no distinction between inputs and...