Multi-step-ahead multivariate predictors: A comparative analysis

10 years 6 months ago
Multi-step-ahead multivariate predictors: A comparative analysis
Abstract-- The focus of this article is to undertake a comparative analysis of multi-step-ahead linear multivariate predictors. The approach considered for the estimation will be based on geometrically reliable linear algebra tools, resorting to subspace identification methods. A crucial issue is quantification of both bias error and variance affecting the estimate of the prediction for increasing values of the look ahead when only a small number of samples is available. No complete theory is available so far, nor sufficient numerical experience. Therefore, the analysis of this paper aims at shading some lights on the topic providing some insights and help to develop some intuitions.
Marzia Cescon, Rolf Johansson
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2010
Where CDC
Authors Marzia Cescon, Rolf Johansson
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