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.
General
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