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Graphical Models for Categorical Data

Paperback / softback

Main Details

Title Graphical Models for Categorical Data
Authors and Contributors      By (author) Alberto Roverato
SeriesSemStat Elements
Physical Properties
Format:Paperback / softback
Pages:178
Dimensions(mm): Height 230,Width 155
Category/GenreProbability and statistics
Databases
Signal processing
ISBN/Barcode 9781108404969
ClassificationsDewey:519.538
Audience
Professional & Vocational
Illustrations Worked examples or Exercises

Publishing Details

Publisher Cambridge University Press
Imprint Cambridge University Press
Publication Date 24 August 2017
Publication Country United Kingdom

Description

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.

Author Biography

Alberto Roverato is Professor of Statistics at Universita di Bologna.

Reviews

'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