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Bayesian Theory and Applications$
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Paul Damien, Petros Dellaportas, Nicholas G. Polson, and David A. Stephens

Print publication date: 2013

Print ISBN-13: 9780199695607

Published to Oxford Scholarship Online: May 2013

DOI: 10.1093/acprof:oso/9780199695607.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 09 May 2021

Hierarchical modelling in time series: the factor analytic approach

Hierarchical modelling in time series: the factor analytic approach

(p.167) 9 Hierarchical modelling in time series: the factor analytic approach
Bayesian Theory and Applications

Gamerman Dani

Salazar Esther

Oxford University Press

This chapter addresses the issue of combining information from a possibly large time series with a factor analytic approach. Each combination of a time series and a factor gives rise to a weight or loading that allows the identification of common features and interpretation of the relationship or correlation structure between the different series. The chapter is organized as follows. Section 9.2 reviews the literature on factor analysis. Section 9.3 presents some basic factor model extensions for modelling high-dimensional multivariate time series. Section 9.4 describes applications of these ideas in the context of spatial analysis. Section 9.5 describes how regression ideas can be incorporated into the factor model setting. Section 9.6 draws some concluding remarks and points at possible directions for further work.

Keywords:   time series, factor analysis, spatial analysis, dynamic factor models

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