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Boekhandel Douwes Den Haag

Chapman & Hall/CRC Texts in Statistical Science

Bayes Rules!

An Introduction to Applied Bayesian Modeling

Ott, Miles Q. (Smith College, Northampton, MA 01063) & Johnson, Alicia A. & Dogucu, Mine (Denison university, OH, USA)

Bayes Rules!

Chapman & Hall/CRC Texts in Statistical Science

Bayes Rules!

An Introduction to Applied Bayesian Modeling

Chapman & Hall/CRC Texts in Statistical Science: Bayes Rules!

 

This book brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, it is an ideal resource for advanced undergraduate statistics students and practitioners with comparable experience.

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Beschrijving Chapman & Hall/CRC Texts in Statistical Science: Bayes Rules!

This book brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, it is an ideal resource for advanced undergraduate statistics students and practitioners with comparable experience. It empowers readers to weave Bayesian approaches into their everyday practice.

ISBN
9781032191591
Pagina's
544
Verschenen
Serie
Chapman & Hall/CRC Texts in Statistical Science
NUR
918
Druk
1
Uitvoering
Hardback
Taal
Engels
Uitgever
Taylor & Francis Ltd

Advanced Computational Methods in Mechanical and Materials Engineering

This book provides in-depth knowledge to solve engineering, geometrical, mathematical, and scientific problems with the help of advanced computational methods with focus on mechanical and materials engineering.

Handbook of Bayesian Variable Selection

The Handbook of Bayesian Variable Selection provides a comprehensive review of theoretical, methodological and computational aspects of Bayesian methods for variable selection. It also provides a valuable reference for all interested in applying existing methods and/or pursuing methodological extensions.

Multiple Imputation of Missing Data in Practice

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies provides a comprehensive introduction to the multiple imputation approach to missing data problems that are often encountered in data analysis.

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