Bayesian Nonparametrics

Bayesian Nonparametrics by J.K. Ghosh, R.V. Ramamoorthi.

Bayesian nonparametrics has grown tremendously in the last three decades, especially in the last few years. This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. While the book is of special interest to Bayesians, it will also appeal to statisticia...

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Bibliographic Details
Main Authors: Ghosh, J.K (Author), Ramamoorthi, R.V (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 2003.
Edition:1st ed. 2003.
Series:Springer Series in Statistics,
Springer eBook Collection.
Subjects:
Statistics .
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Introduction: Why Bayesian Nonparametrics—An Overview and Summary
  • Preliminaries and the Finite Dimensional Case
  • M(?) and Priors on M(?)
  • Dirichlet and Polya tree process
  • Consistency Theorems
  • Density Estimation
  • Inference for Location Parameter
  • Regression Problems
  • Uniform Distribution on Infinite-Dimensional Spaces
  • Survival Analysis—Dirichlet Priors
  • Neutral to the Right Priors
  • Exercises.

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