Bayesian nonparametric data analysis
The book provides a rich review of Bayesian nonparametric methods and models with a wealth of illustrations ranging from simple examples to more elaborated applications on case studies considered in recent literature. The focus is on data analysis and the material is organised accordingly, with chapters corresponding to specific inferential problems such as density estimation, regression, analysis of categorical data, survival problems, classification, clustering and feature allocation. For each inferential problem an up-to-date account of Bayesian nonparametric methodologies is presented by means of a rich set of illustrative examples. Computational methods for the implementation of such models are extensively discussed and pointers to available software are also provided. Considering the growing interest in Bayesian nonparametric models and the rich literature production that has characterised this area in the last three decades, the book succeeds in the difficult task of providing a rather complete, yet coincise, overview. Overall, the nature of the book makes it a suitable reference for both practitioners and theorists.
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