Overview
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones.The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.
The book, Bayesian Nonparametric Data Analysis (Springer Series in Statistics) [Bulk, Wholesale, Quantity] ISBN#9783319368429 in Paperback by Peter Müller, Fernando Andres Quintana, Alejandro Jara, Tim Hanson may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.
Details
Format:
Paperback
Publication Date:
10/15/2016
ISBN-13:
9783319368429
Pages:
193
Publisher:
Springer International Publishing
