Approximate bayesian computation using auxiliary model based estimates
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IWSM_ABC_Paper.pdf. |
Description
We present a novel approach for developing summary statistics for use in approximate Bayesian computation (ABC) algorithms using indirect infer- ence. We embed this approach within a sequential Monte Carlo algorithm that is completely adaptive. This methodological development was motivated by an application involving data on macroparasite population evolution modelled with a trivariate Markov process. The main objective of the analysis is to compare inferences on the Markov process when considering two di®erent indirect mod- els. The two indirect models are based on a Beta-Binomial model and a three component mixture of Binomials, with the former providing a better ¯t to the observed data.
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| ID Code: | 69026 | ||||
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| Item Type: | Chapter in Book, Report or Conference volume (Conference contribution) | ||||
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| Measurements or Duration: | 6 pages | ||||
| Pure ID: | 32148963 | ||||
| Divisions: | Past > QUT Faculties & Divisions > Faculty of Science and Technology Past > QUT Faculties & Divisions > Science & Engineering Faculty Current > Research Centres > Australian Research Centre for Aerospace Automation |
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| Copyright Owner: | Copyright 2010 [please consult the author] | ||||
| Copyright Statement: | This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au | ||||
| Deposited On: | 23 Mar 2014 23:24 | ||||
| Last Modified: | 02 Mar 2024 00:12 |
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