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An Introduction to Bayesian Scientific Computing Daniela Calvetti

An Introduction to Bayesian Scientific Computing By Daniela Calvetti

An Introduction to Bayesian Scientific Computing by Daniela Calvetti


Summary

The book's highly accessible approach makes it particularly ideal if you want to become acquainted with the Bayesian approach to computational science, but do not need to be fully immersed in detailed statistical analysis.

An Introduction to Bayesian Scientific Computing Summary

An Introduction to Bayesian Scientific Computing: Ten Lectures on Subjective Computing by Daniela Calvetti

This book has been written for undergraduate and graduate students in various disciplines of mathematics. The authors, internationally recognized experts in their field, have developed a superior teaching and learning tool that makes it easy to grasp new concepts and apply them in practice. The book's highly accessible approach makes it particularly ideal if you want to become acquainted with the Bayesian approach to computational science, but do not need to be fully immersed in detailed statistical analysis.

An Introduction to Bayesian Scientific Computing Reviews

From the reviews:

This witty, erudite, and surprisingly practical book is made up of ten chapters. ... A central topic of the book is the relationship between statistical inference and the inverse problems that define Bayesian (subjective) statistics. ... This excellent book will be valuable to scientists of various stripes, statisticians, numerical analysts, those who work in image processing, and those who implement Bayesian belief nets. (George Hacken, ACM Computing Reviews, Vol. 49 (11), November, 2008)

Introduction to Bayesian Scientific Computing is a 200-page, easily accessible, pleasant introduction fusing Bayesian approaches with numerical linear algebra methods for inverse problems ... . What I like most about this book is the apparent enthusiasm of the authors and their genuine interest in explaining rather than showing off. This enthusiasm is contagious, and the result is very readable. (Uri Ascher, The Mathematical Intelligencer, Vol. 31 (1), 2009)

Table of Contents

Inverse problems and subjective computing.- Basic problem of statistical inference.- The praise of ignorance: randomness as lack of information.- Basic problem in numerical linear algebra.- Sampling: first encounter.- Statistically inspired preconditioners.- Conditional Gaussian densities and predictive envelopes.- More applications of the Gaussian conditioning.- Sampling: the real thing.- Wrapping up: hypermodels, dynamic priorconditioners and Bayesian learning.

Additional information

NLS9780387733937
9780387733937
0387733930
An Introduction to Bayesian Scientific Computing: Ten Lectures on Subjective Computing by Daniela Calvetti
New
Paperback
Springer-Verlag New York Inc.
2007-11-26
202
N/A
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