A book edited by Yanan Fan and Scott Sisson was published earlier this month. 

Handbook of Approximate Bayesian Computation, co-edited with University of Bristol Professor of Statistics Mark Beaumont, is a compilation of articles by 49 contributors at the forefront of ABC research and application. 

The volume was published by Chapman and Hall/CRC, who provide the following summary of the book:

As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of ABC methods. These simple, but powerful statistical techniques, take Bayesian statistics beyond the need to specify overly simplified models, to the setting where the model is defined only as a process that generates data. This process can be arbitrarily complex, to the point where standard Bayesian techniques based on working with tractable likelihood functions would not be viable. ABC methods finesse the problem of model complexity within the Bayesian framework by exploiting modern computational power, thereby permitting approximate Bayesian analyses of models that would otherwise be impossible to implement.

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.


Congratulations to Yanan and Scott upon the publication of their book, which looks set to become an important contribution to the field.