Computing the best linear predictor in a Hilbert space. Applications to general ARMAH processes

D. Bosq

Journal of Multivariate Analysis, 2014, vol. 124, issue C, 436-450

Abstract: This article deals with linear prediction in large dimensions. One obtains various explicit forms of the best linear predictor in a Hilbert space. The difficulty comes from the fact that the associated linear operator is, in general, not continuous. Applications to ARMAH processes, models with noise and Bayesian estimators are considered.

Keywords: Functional filters; Hilbert spaces; Linear processes; Measurable linear transformations; Prediction; Large dimensions (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (5)

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DOI: 10.1016/j.jmva.2013.11.013

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