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    Rights statement: This is the peer reviewed version of the following article:Neal, P., and Xiang, F. (2017) Collapsing of Non-centred Parameterized MCMC Algorithms with Applications to Epidemic Models. Scand J Statist, 44: 81–96. doi: 10.1111/sjos.12242 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/sjos.12242/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Collapsing of non-centered parameterised MCMC algorithms with applications to epidemic models

Research output: Contribution to journalJournal articlepeer-review

Published
<mark>Journal publication date</mark>03/2017
<mark>Journal</mark>Scandinavian Journal of Statistics
Issue number1
Volume44
Number of pages16
Pages (from-to)81-96
Publication StatusPublished
Early online date2/09/16
<mark>Original language</mark>English

Abstract

Data augmentation is required for the implementation of many MCMC algorithms. The inclusion of augmented data can often lead to conditional distributions from well-known probability distributions for some of the parameters in the model.
In such cases, collapsing (integrating out parameters) has been shown to improve the performance of MCMC algorithms. We show how integrating out the infection rate parameter in epidemic models leads to efficient MCMC algorithms for two very different epidemic scenarios, final outcome data from a multitype SIR epidemic and longitudinal data from a spatial SI epidemic. The resulting MCMC algorithms give fresh insight into real life epidemic data sets.

Bibliographic note

This is the peer reviewed version of the following article:Neal, P., and Xiang, F. (2017) Collapsing of Non-centred Parameterized MCMC Algorithms with Applications to Epidemic Models. Scand J Statist, 44: 81–96. doi: 10.1111/sjos.12242 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/sjos.12242/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.