Bayesian Nonparametric Data Analysis Softcover Repri Edition Contributor(s): Müller, Peter (Author), Quintana, Fernando Andres (Author), Jara, Alejandro (Author) |
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ISBN: 3319368427 ISBN-13: 9783319368429 Publisher: Springer OUR PRICE: $113.99 Product Type: Paperback - Other Formats Published: October 2016 |
Additional Information |
BISAC Categories: - Mathematics | Probability & Statistics - General - Computers | Mathematical & Statistical Software - Medical | Biostatistics |
Dewey: 519.5 |
Series: Springer Statistics |
Physical Information: 0.44" H x 6.14" W x 9.21" (0.66 lbs) 193 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. |