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Abstract Details

Activity Number: 385
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
Sponsor: Business and Economic Statistics Section
Abstract - #304783
Title: Reduced-Rank Time-Series Models
Author(s): Victor Solo*+
Companies: University of New South Wales
Address: School of Electrical Engineering, 2033 Kensington, , Australia
Keywords: time series ; factor model ; reduced rank

The recent interest in high dimensional time-series driven particularly by work on dynamic factor models leads naturally to a reconsideration of reduced rank time-series models. Existing reduced rank vector time-series models are essentially constrained VAR models. Here we characterize these models in state space terms in a very simple way and thus obtain an extension to the vector ARMA case. We discuss two new associated state space subspace fitting algorithms. We also discuss the close relation to dynamic factor models.

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