Fundamentals of Nonparametric Bayesian Inference

Discover the essential insights of Fundamentals of Nonparametric Bayesian Inference by Subhashis Ghosal, published by Cambridge University Press in 2017. This comprehensive hardback edition spans 670 pages and serves as an authoritative resource on Bayesian nonparametrics, a versatile framework crucial for inference in statistics and machine learning. Ideal for graduate-level courses, this self-contained text includes helpful appendices that cover necessary prerequisites and a wealth of exercises to reinforce learning. Its practical applications extend across various scientific disciplines, including economics and biostatistics, making it an invaluable addition to your academic library. Enhance your understanding of this pivotal area in statistical theory and practice with Ghosal's expert guidance.