Handbook of Approximate Bayesian Computation

The Handbook of ABC provides illuminating insight into the world of Bayesian modelling for intractable models for both experts and newcomers alike. It is an essential reference book for anyone interested in learning about and implementing ABC techniques to analyse complex models in the modern world.

Introduction
Overview of approximate Bayesian computation: S. A. Sisson, Y. Fan and M. A. Beaumont
On the history of ABC: S.Tavar e
Regression approaches: M. G. B. Blum
Monte Carlo samplers for ABC: Y. Fan and S. A. Sisson
Summary statistics: D. Prangle
Likelihood-free model choose: J.-M. Marin, P. Pudlo, A. Estoup and C. Robert
ABC and indirect inference: C. C. Drovandi
High-dimensional ABC: D. Nott, V. Ong, Y. Fan and S. A. Sisson Theoretical and methodological aspects of MCMC computations with noisy likelihoods: C. Andrieu, A.Lee and M. Viola
Informed Choices: How to calibrate ABC with hypothesis testing: O. Ratmann, A. Camacho, S. Hu and C. Coljin
Approximating the likelihood in approximate Bayesian computation: C. C. Drovandi, C. Grazian, K. Mengersen and C. Robert
Software: D.Wegmann
Divide and conquer in ABC: Expectation-Propagation algorithms for likelihood-free inference: S. Barthelm e, N. Chopin and V. Cottet
SMC-ABC methods for estimation of stochastic simulation models of the limit order book: G.W. Peters, E. Panayi and F. Septier
Inferences on the acquisition of multidrug resistance in Mycobacterium tuberculosis using molecular epidemiological data: G. S. Rodrigues, S. A. Sisson, M. M. Tanaka
ABC in Systems Biology: J. Liepe and M. P. H. Stumpf
Application of approximate Bayesian computation to make inference about the genetic history of Pygmy hunter-gatherers populations from Western Central Africa: A. Estoup et al
ABC for climate: dealing with expensive simulators: P. B. Holden, N. R. Edwards, J. Hensman and R. D. Wilkinson
ABC in ecological modelling: M. Fasiolo and S. N. Wood
ABC in Nuclear Imaging: Y. Fan, S. R. Meikle, G. Angelis and A. Sitek