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2007 Modelling High-Dimensional Time Series by Generalized Linear Dynamic Factor Models: An Introductory Survey
Manfred Deistler, Christiane Zinner
Commun. Inf. Syst. 7(2): 153-166 (2007).

Abstract

Factor models are used to condense high dimensional data consisting of many vari ables into a much smaller number of factors. Here we present an introductory survey to factor models for time series, where the factors represent the comovement between the single time series. Principal component analysis, linear dynamic factor models with idiosyncratic noise and generalized linear dynamic factor models are introduced and structural properties, such as identifiability, as well as estimation are discussed.

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Manfred Deistler. Christiane Zinner. "Modelling High-Dimensional Time Series by Generalized Linear Dynamic Factor Models: An Introductory Survey." Commun. Inf. Syst. 7 (2) 153 - 166, 2007.

Information

Published: 2007
First available in Project Euclid: 20 July 2007

zbMATH: 1141.62065
MathSciNet: MR2344194

Rights: Copyright © 2007 International Press of Boston

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Vol.7 • No. 2 • 2007
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