%0 Journal Article
%A García Hiernaux, Alfredo Alejandro
%A Casals, José
%A Jerez Méndez, Miguel
%T Identification of Canonical Models for Vectors of Time Series: A Subspace Approach
%D 2023
%@ 0932-5026
%U https://hdl.handle.net/20.500.14352/72171
%X We propose a new method to specify linear models for vectors of time series with some convenient properties. First, it provides a unified modeling approach for single and multiple time series, as the same decisions are required in both cases. Second, it is scalable, meaning that it provides a quick preliminary model, which can be refined in subsequent modeling phases if required. Third, it is optionally automatic, because the specification depends on a few key parameters which can be determined either automatically or by human decision. And last, it is parsimonious, as it allows one to choose and impose a canonical structure by a novel estimation procedure. Several examples with simulated and real data illustrate its application in practice.
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