Graphical Models for Categorical Data

Alberto Roverato (Università di Bologna)

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English

Cambridge University Press
24 August 2017

Probability & statistics; Databases; Data mining; Signal processing

Series: SemStat Elements

For advanced students of network data science, this compact account covers both well-established methodology and the theory of models recently introduced in the graphical model literature. It focuses on the discrete case where all variables involved are categorical and, in this context, it achieves a unified presentation of classical and recent results.

By: Alberto Roverato (Università di Bologna)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Dimensions: Height: 230mm, Width: 155mm, Spine: 10mm
Weight: 240g
ISBN: 9781108404969
ISBN 10: 1108404960
Series: SemStat Elements
Pages: 178
Publication Date: 24 August 2017
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Alberto Roverato is Professor of Statistics at Università di Bologna.

Reviews for Graphical Models for Categorical Data

'Graphical Models for Categorical Data is a concise introduction to the theory of graphical models. The book is a perfect read for those who want better grasp of the basics of graphical models for discrete data. ... The main strength of the book is the unified notation, which helps the reader draw links between various approaches to graphical models for discrete data. The book also exploits the link between the theory of graphical models and the more general theory of statistical exponential families. This makes it an extremely valuable addition to the current literature and a useful tool for future research.' Piotr Zwiernik, Mathematical Reviews