Dependence Models via Hierarchical Structures - Couverture rigide

Nieto-Barajas, Luis E.

Couverture rigide

ISBN 10 : 1009584111 ISBN 13 : 9781009584111

Editeur : Cambridge University Press, 2025

Synopsis

Bringing together years of research into one useful resource, this text empowers the reader to creatively construct their own dependence models. Intended for senior undergraduate and postgraduate students, it takes a step-by-step look at the construction of specific dependence models, including exchangeable, Markov, moving average and, in general, spatio-temporal models. All constructions maintain a desired property of pre-specifying the marginal distribution and keeping it invariant. They do not separate the dependence from the marginals and the mechanisms followed to induce dependence are so general that they can be applied to a very large class of parametric distributions. All the constructions are based on appropriate definitions of three building blocks: prior distribution, likelihood function and posterior distribution, in a Bayesian analysis context. All results are illustrated with examples and graphical representations. Applications with data and code are interspersed throughout the book, covering fields including insurance and epidemiology.

A propos du livre

À propos de l?auteur

Luis E. Nieto-Barajas is Full Professor and Head of the Department of Statistics at the Instituto Tecnológico Autónomo de México (ITAM). He was previously President of the Mexican Statistical Association (2020-2021). For his thesis, he won the Savage Award (2001) and Francisco Aranda Ordaz Awards (2002-2004).

Détails de l'édition

• Éditeur: Cambridge University Press
• Date d'édition: 2025
• Langue: anglais
• ISBN 10: 1009584111
• ISBN 13: 9781009584111
• Reliure: Relié
• Nombre de pages: 149
• Coordonnées du fabricant: Cambridge University Press; https://www.cambridge.org/; ; Via Honduras,15; Pomezia; Italia; 71; Italie