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Modelling seasonal patterns in longitudinal profiles with correlated random walks

Type of publication Not peer-reviewed
Publikationsform Other publication (non peer-review)
Publication date 2011
Author Riebler Andrea, Held Leonhard, Rue Håvard,
Project Multivariate analysis of dependent count data
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Other publication (non peer-review)

Book Modelling seasonal patterns in longitudinal profiles with correlated random walks
Publisher Proceedings of the 26th International Workshop on Statistical Modelling, Valencia Spain
ISBN 978-84-694-5129-8

Abstract

Seasonal patterns, as they occur in time series of infectious disease surveillance counts, are frequently modelled using a superposition of sine and cosine functions. However, in some cases this might be too simple. We propose the use of circular second order random walks instead and extend this approach to multivariate time series of counts. A correlated Gaussian Markov random field approach combines a uniform correlation matrix with a circular random walk to allow the seasonal pattern to be similar across regions, say, but not identical. Thus, spatially-varying disease onsets may be accounted for. The methodology is applied to weekly number of deaths from influenza and pneumonia in nine major regions of the USA.
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