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Bayesian Nonparametric Data Analysis

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 d...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Müller, Peter (Author), Quintana, Fernando Andres (Author), Jara, Alejandro (Author), Hanson, Tim (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: Cham : Springer International Publishing : Imprint: Springer, 2015.
Edition:1st ed. 2015.
Series:Springer Series in Statistics,
Subjects:
Online Access:Texto Completo
Table of Contents:
  • 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.