Prior Processes and Their Applications: Nonparametric Bayesian Estimation (Springer Series in Statistics) - Image 1

£91.60

It has never been this cheap. We have no record of a lower price.

£92 today · cheaper than every other day in the last 3 months

Springer Prior Processes and Their Applications: Nonparametric Bayesian Estimation (Springer Series in Statistics)

Name: Prior Processes and Their Applications: Nonparametric Bayesian Estimation (Springer Series in Statistics)
Brand: Springer
Price: 91.6 GBP
Availability: InStock

Medical & Healthcare Practitioners

Price Distribution

Price distribution over 41 days • 1 price levels

Days at Price

Price Analysis

Most common price: £92 (41 days, 100.0%)

Price range: £92 - £92

Price levels: 1 different prices over 41 days

Description

This book presents a systematic and comprehensive treatment of various prior processes that have been developed over the past four decades for dealing with Bayesian approach to solving selected nonparametric inference problems. This revised edition has been substantially expanded to reflect the current interest in this area. After an overview of different prior processes, it examines the now pre-eminent Dirichlet process and its variants including hierarchical processes, then addresses new processes such as dependent Dirichlet, local Dirichlet, time-varying and spatial processes, all of which exploit the countable mixture representation of the Dirichlet process. It subsequently discusses various neutral to right type processes, including gamma and extended gamma, beta and beta-Stacy processes, and then describes the Chinese Restaurant, Indian Buffet and infinite gamma-Poisson processes, which prove to be very useful in areas such as machine learning, information retrieval and featural modeling. Tailfree and Polya tree and their extensions form a separate chapter, while the last two chapters present the Bayesian solutions to certain estimation problems pertaining to the distribution function and its functional based on complete data as well as right censored data. Because of the conjugacy property of some of these processes, most solutions are presented in closed form. However, the current interest in modeling and treating large-scale and complex data also poses a problem – the posterior distribution, which is essential to Bayesian analysis, is invariably not in a closed form, making it necessary to resort to simulation. Accordingly, the book also introduces several computational procedures, such as the Gibbs sampler, Blocked Gibbs sampler and slice sampling, highlighting essential steps of algorithms while discussing specific models. In addition, it features crucial steps of proofs and derivations, explains the relationships between different processes and provides further clarifications to promote a deeper understanding. Lastly, it includes a comprehensive list of references, equipping readers to explore further on their own.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3319327887
Category: Books > Subjects > Health, Family & Lifestyle > Medical & Healthcare Practitioners
Domain: Amazon UK
Release Date: 19 August 2016
Listed Since: 10 March 2016

Barcode

No barcode data available

It has never been this cheap. We have no record of a lower price.

Springer Prior Processes and Their Applications: Nonparametric Bayesian Estimation (Springer Series in Statistics)

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Bayesian Statistical Methods: With Applications to Machine Learning (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Statistics: An Introduction, 4th Edition

CRC Press Markov Chain Monte Carlo - Bayesian Inference Book

Probability and Statistical Inference: From Basic Principles to Advanced Models (Chapman & Hall/CRC Texts in Statistical Science)

Probability and Statistical Inference - CRC Press Textbook

Current Trends in Bayesian Methodology with Applications

Introduction to Statistical Modelling and Inference

Bayesian Nonparametrics - Springer Series in Statistics

Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Statistics from Methods to Models and Applications: Research from BAYSM 2014: 126 (Springer Proceedings in Mathematics & Statistics, 126)

An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics)

Bayesian Programming (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Bayesian Nonparametric Statistics: Theorems, Proofs, and Python Implementations (Computational Mathematics Library)

Understanding Computational Bayesian Statistics (Wiley Series in Computational Statistics)

Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Statistics for Experimental Scientists: A General Introduction Using Distribution-Free Methods

Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians (Chapman & Hall/CRC Texts in Statistical Science)

Objective Bayesian Inference

Cambridge Fundamentals of Nonparametric Bayesian Inference Book

Introduction to Applied Bayesian Statistics for Social Scientists

Topics on Methodological and Applied Statistical Inference - Springer

Bayesian Nonparametrics (Springer Series in Statistics)

Probability and Statistical Inference (Wiley Series in Probability and Statistics)

Bayesian Econometric Modelling for Big Data - Chapman and Hall/CRC

It has never been this cheap. We have no record of a lower price.

Springer Prior Processes and Their Applications: Nonparametric Bayesian Estimation (Springer Series in Statistics)

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Bayesian Statistical Methods: With Applications to Machine Learning (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Statistics: An Introduction, 4th Edition

CRC Press Markov Chain Monte Carlo - Bayesian Inference Book

Probability and Statistical Inference: From Basic Principles to Advanced Models (Chapman & Hall/CRC Texts in Statistical Science)

Probability and Statistical Inference - CRC Press Textbook

Current Trends in Bayesian Methodology with Applications

Introduction to Statistical Modelling and Inference

Bayesian Nonparametrics - Springer Series in Statistics

Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Statistics from Methods to Models and Applications: Research from BAYSM 2014: 126 (Springer Proceedings in Mathematics & Statistics, 126)

An Introduction to Bayesian Analysis: Theory and Methods (Springer Texts in Statistics)

Bayesian Programming (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Bayesian Nonparametric Statistics: Theorems, Proofs, and Python Implementations (Computational Mathematics Library)

Understanding Computational Bayesian Statistics (Wiley Series in Computational Statistics)

Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Statistics for Experimental Scientists: A General Introduction Using Distribution-Free Methods

Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians (Chapman & Hall/CRC Texts in Statistical Science)

Objective Bayesian Inference

Cambridge Fundamentals of Nonparametric Bayesian Inference Book

Introduction to Applied Bayesian Statistics for Social Scientists

Topics on Methodological and Applied Statistical Inference - Springer

Bayesian Nonparametrics (Springer Series in Statistics)

Probability and Statistical Inference (Wiley Series in Probability and Statistics)

Bayesian Econometric Modelling for Big Data - Chapman and Hall/CRC