Müller / Quintana / Jara

Bayesian Nonparametric Data Analysis

2015. Buch. xiv, 193 S.: 49 s/w-Abbildungen, 10 Farbabbildungen, Bibliographien. Hardcover
Springer ISBN 978-3-319-18967-3
Format (B x L): 15,5 x 23,5 cm
Gewicht: 479 g
In englischer Sprache
Das Werk ist Teil der Reihe:
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.



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This is the first text to introduce nonparametric Bayesian inference from a data analysis perspective Includes a large number of examples to illustrate the application of nonparametric Bayesian models for important statistical inference Problems Features an extensive discussion of computational details for a practical implementation, including R code for many of the examples