dc.contributor.author | Andrianakis, I | |
dc.contributor.author | Vernon, I | |
dc.contributor.author | McCreesh, N | |
dc.contributor.author | McKinley, TJ | |
dc.contributor.author | Oakley, J | |
dc.contributor.author | Nsubuga, R | |
dc.contributor.author | Goldstein, M | |
dc.contributor.author | White, R | |
dc.date.accessioned | 2016-11-14T09:43:11Z | |
dc.date.issued | 2016-11-24 | |
dc.description.abstract | Complex stochastic models are commonplace in epidemiology, but their utility depends on their
calibration to empirical data. History matching is a (pre-)calibration method that has been applied
successfully to complex deterministic models. In this work, we adapt history matching to stochastic
models, by emulating the variance in the model outputs, and therefore accounting for its dependence
on the model’s input values. The proposed method is applied to a real complex epidemiological model
of HIV in Uganda with 22 inputs and 18 outputs, and is found to increase the efficiency of history
matching, requiring 70% of the time and 43% fewer simulator evaluations compared to a previous
variant of the method. The insight gained into the structure of the HIV model, and the constraints
placed upon it, are then discussed. | en_GB |
dc.description.sponsorship | This work was funded by the UK Medical Research Council (MRC) and the UK Department for
International Development (DFID) under the MRC/DFID Concordat agreement that is also part of
the EDCTP2 programme supported by the European Union (MR/J005088/1). RGW is additionally
funded by the Bill and Melinda Gates Foundation (TB Modelling and Analysis Consortium:
OPP1084276) and UNITAID (4214-LSHTM-Sept15; PO #8477-0-600). | en_GB |
dc.identifier.citation | Published online 24 November 2016 | en_GB |
dc.identifier.doi | 10.1111/rssc.12198 | |
dc.identifier.uri | http://hdl.handle.net/10871/24396 | |
dc.language.iso | en | en_GB |
dc.publisher | Wiley for Royal Statistical Society | en_GB |
dc.rights | © 2017 The Authors Journal of the Royal Statistical Society: Series C Applied Statistics published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. | |
dc.subject | Calibration | en_GB |
dc.subject | Gaussian processes | en_GB |
dc.subject | Stochastic simulators | en_GB |
dc.subject | Inverse problems | en_GB |
dc.subject | Individual based models | en_GB |
dc.title | History matching of a complex epidemiological model of HIV transmission using variance emulation | en_GB |
dc.type | Article | en_GB |
dc.identifier.issn | 1467-9876 | |
dc.description | This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record. | |
dc.identifier.journal | Journal of the Royal Statistical Society Series C: Applied Statistics | en_GB |