๐”– Scriptorium
โœฆ   LIBER   โœฆ

๐Ÿ“

Bayesian Nonparametrics (Springer Series in Statistics)

โœ Scribed by J.K. Ghosh, R.V. Ramamoorthi


Publisher
Springer
Year
2003
Tongue
English
Leaves
319
Series
Springer Series in Statistics
Edition
1
Category
Library

โฌ‡  Acquire This Volume

No coin nor oath required. For personal study only.

โœฆ Synopsis


This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian non-parametrics.


๐Ÿ“œ SIMILAR VOLUMES


Bayesian Survival Analysis (Springer Ser
โœ Joseph G. Ibrahim, Ming-Hui Chen, Debajyoti Sinha ๐Ÿ“‚ Library ๐Ÿ“… 2010 ๐Ÿ› Springer ๐ŸŒ English

Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. It presents a balance between theory and applications, and for each class of models discu

Introduction to Nonparametric Estimation
โœ Alexandre B. Tsybakov ๐Ÿ“‚ Library ๐Ÿ“… 2008 ๐ŸŒ English

This is a concise text developed from lecture notes and ready to be used for a course on the graduate level. The main idea is to introduce the fundamental concepts of the theory while maintaining the exposition suitable for a first approach in the field. Therefore, the results are not always given i

Statistical Decision Theory and Bayesian
โœ James O. Berger ๐Ÿ“‚ Library ๐Ÿ“… 1985 ๐Ÿ› Springer-Verlag ๐ŸŒ English

In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used

Applied Nonparametric Statistics in Reli
โœ Gรกmiz ๐Ÿ“‚ Library ๐Ÿ“… 2011 ๐Ÿ› Springer ๐ŸŒ English

<p><span>Nonparametric statistics has probably become the leading methodology for researchers performing data analysis. It is nevertheless true that, whereas these methods have already proved highly effective in other applied areas of knowledge such as biostatistics or social sciences, nonparametric