Handbook of Approximate Bayesian Computation (Chapman & Hall/CRC Handbooks of Modern Statistical Methods) - Softcover

Softcover

ISBN 10: 0367733722 ISBN 13: 9780367733728

Publisher: Routledge, 2020

Synopsis

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.

About this title

About the Author

Scott Sission is Professor, ARC Future Fellow and Head of Statistics in the School of Mathematics and Statistics at UNSW.

Yanan Fan is a Senior Lecturer at the School of Mathematics and Statistics at UNSW.

Mark Beaumont is Professor of Statistics at the University of Bristol.

Edition details

• Publisher: Routledge
• Publication date: 2020
• Language: English
• ISBN 10: 0367733722
• ISBN 13: 9780367733728
• Binding: Paperback
• Edition number: 1
• Number of pages: 680
• Editor: Sisson Scott A., Fan Yanan, Beaumont Mark