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

ISBN 10: 0367733722 / ISBN 13: 9780367733728

Editore: Taylor & Francis Group, 2020

Riguardo questo articolo

pp. 678.

Codice articolo 26384623290

Dati bibliografici

• Titolo: Handbook of Approximate Bayesian Computation (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
• Editore: Taylor & Francis Group
• Data di pubblicazione: 2020
• Lingua: Inglese
• ISBN 10: 0367733722
• ISBN 13: 9780367733728
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

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.

Informazioni sull?autore

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.