Approximate Bayesian computation using auxiliary model based estimates

Pettitt, Anthony N., Drovandi, Christopher C., & Faddy, Malcolm (2010) Approximate Bayesian computation using auxiliary model based estimates. In Bowman, Adrian (Ed.) Proceedings of the 25th International Workshop on Statistical Modelling, University of Glasgow, Glasgow, pp. 433-438.

View at publisher (open access)

Abstract

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.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

47 since deposited on 23 Mar 2014
4 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 69026
Item Type: Conference Paper
Refereed: Yes
Keywords: Approximate Bayesian computation, Beta-Binomial model, Binomial mixture model, Indirect inference, Markov process, Sequential Monte Carlo
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400)
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2010 [please consult the author]
Deposited On: 23 Mar 2014 23:24
Last Modified: 19 Jun 2014 23:33

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page