Overview
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.
Full Product Details
Author: Alberto Roverato (Università di Bologna)
Publisher: Cambridge University Press
Imprint: Cambridge University Press
Dimensions:
Width: 15.50cm
, Height: 1.00cm
, Length: 23.00cm
Weight: 0.240kg
ISBN: 9781108404969
ISBN 10: 1108404960
Pages: 178
Publication Date: 24 August 2017
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
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 '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
'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
Author Information
Alberto Roverato is Professor of Statistics at Università di Bologna.
