Handbook of Graphical Models

Marloes Maathuis

ISBN 10: 0367732602 / ISBN 13: 9780367732608

Verlag: CRC Press, 2020

Beschreibung

nach der Bestellung gedruckt Neuware - Printed after ordering - 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.Features:Contributions by leading researchers from a range of disciplinesStructured in five parts, covering foundations, computational aspects, statistical inference, causal inference, and applicationsBalanced coverage of concepts, theory, methods, examples, and applicationsChapters can be read mostly independently, while cross-references highlight connectionsThe handbook is targeted at a wide audience, including graduate students, applied researchers, and experts in graphical models.

Bestandsnummer des Verkäufers 9780367732608

Bibliografische Details

• Titel: Handbook of Graphical Models
• Verlag: CRC Press
• Erscheinungsjahr: 2020
• Sprache: Englisch
• ISBN-10: 0367732602
• ISBN-13: 9780367732608
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 254B x 178 H x 30 T Millimeter Breite: 254 mm, Höhe: 178 mm, Tiefe: 30 mm
• Gewicht: 1032 Gramm

Über diesen Titel

Inhaltsangabe

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.

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.

Über die Autorin bzw. den Autor

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.