Handbook of Graphical Models - Couverture rigide

 
9781498788625: Handbook of Graphical Models

Synopsis

A graphical model is a statistical model that is represented by a graph. The factorization properties underlying graphical models facilitate tractable computation with multivariate distributions, making the models a valuable tool with a plethora of applications. Furthermore, directed graphical models allow intuitive causal interpretations and have become a cornerstone for causal inference.

While there exist a number of excellent books on graphical models, the field has grown so much that individual authors can hardly cover its entire scope. Moreover, the field is interdisciplinary by nature. Through chapters by leading researchers from different areas, this handbook provides a broad and accessible overview of the state of the art.

Key features:

* Contributions by leading researchers from a range of disciplines

* Structured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applications

* Balanced coverage of concepts, theory, methods, examples, and applications

* Chapters can be read mostly independently, while cross-references highlight connections

The handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l?auteur

Marloes Maathuis is Professor of Statistics at ETH Zurich.

Mathias Drton is Professor of Statistics at the University of Copenhagen and the University of Washington.

Steffen Lauritzen is Professor of Statistics at the University of Copenhagen.

Martin Wainwright is Chancellor's Professor at the University of Berkeley.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Autres éditions populaires du même titre

9780367732608: Handbook of Graphical Models

Edition présentée

ISBN 10 :  0367732602 ISBN 13 :  9780367732608
Editeur : CRC Press, 2020
Couverture souple