Statistics and Computing

, Volume 22, Issue 6, pp 1199–1207 | Cite as

Improving ABC for quantile distributions

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Abstract

A new approximate Bayesian computation (ABC) algorithm is proposed specifically designed for models involving quantile distributions. The proposed algorithm compares favourably with two other ABC algorithms when applied to examples involving quantile distributions.

Keywords

Approximate Bayesian computation Likelihood-free inference Markov chain Monte Carlo Quantile distributions Quantile regression 

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.School of Mathematics and PhysicsUniversity of QueenslandBrisbaneAustralia

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