Handbook of Graphical Models (Hardcover)

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.

General

Imprint:	Productivity Press
Country of origin:	United States
Series:	Chapman & Hall/CRC Handbooks of Modern Statistical Methods
Release date:	November 2018
First published:	2019
Editors:	Marloes Maathuis • Mathias Drton • Steffen Lauritzen • Martin Wainwright
Dimensions:	254 x 178 x 40mm (L x W x T)
Format:	Hardcover
Pages:	536
ISBN-13:	978-1-4987-8862-5
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General
LSN:	1-4987-8862-9
Barcode:	9781498788625

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