TY  - BOOK
AU  - Müller,Peter
AU  - Quintana,Fernando Andres
AU  - Jara,Alejandro
AU  - Hanson,Tim
ED  - SpringerLink (Online service)
TI  - Bayesian Nonparametric Data Analysis
T2  - Springer Series in Statistics,
SN  - 9783319189680
AV  - QA276-280 
U1  - 519.5 23
PY  - 2015///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Statistics
KW  - Statistical Theory and Methods
KW  - Statistics and Computing/Statistics Programs
KW  - Statistics for Life Sciences, Medicine, Health Sciences
N1  - Preface -- Acronyms -- 1.Introduction -- 2.Density Estimation - DP Models -- 3.Density Estimation - Models Beyond the DP -- 4.Regression -- 5.Categorical Data -- 6.Survival Analysis -- 7.Hierarchical Models -- 8.Clustering and Feature Allocation -- 9.Other Inference Problems and Conclusions -- Appendix: DP package
N2  - 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 on-line software pages
UR  - http://dx.doi.org/10.1007/978-3-319-18968-0
ER  -