Bayesian Methods for the Physical Sciences: Learning from Examples in Astronomy and Physics by Stefano AndreonBayesian Methods for the Physical Sciences: Learning from Examples in Astronomy and Physics by Stefano Andreon

Bayesian Methods for the Physical Sciences: Learning from Examples in Astronomy and Physics

byStefano Andreon, Brian Weaver

Hardcover | June 2, 2015

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Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications.

This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics.

Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University

Stefano Andreon is an astronomer of the National Institute of Astrophysics, Brera Observatory (Milan, Italy). Stefano's research is focused on understanding the evolution of galaxies and of galaxy clusters, near and far, and adopting Bayesian methods. He also teaches Bayesian methods to PhD students of various Italian and French Univer...
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Title:Bayesian Methods for the Physical Sciences: Learning from Examples in Astronomy and PhysicsFormat:HardcoverDimensions:238 pagesPublished:June 2, 2015Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319152866

ISBN - 13:9783319152868

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Table of Contents

?Recipes.- A Bit of Theory.- A Bit of Numerical Computation.- Single Parameter Models.- The Prior.- Multi-parameters Models.- Non-random Data Collection.- Fitting Regression Models.- Model Checking and Sensitivity Analysis.- Bayesian vs Simple Methods.- Appendix: Probability Distributions.- Appendix: The third axiom of probability, conditional probability, independence and conditional independence.

Editorial Reviews

Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications.This book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics.Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State UniversityBayesian statistical methods are fast becoming the statistical method of choice among the majority of physicists and astrophysicists who find they must statistically evaluate their study data. Bayesian Methods for the Physical Sciences is co-authored by a noted astrophysicist and an accomplished Los Alamos statistician who specializes in this area of application. Together they have produced a true guidebook to the Bayesian modeling of astrophysical data. JAGS code is used and displayed for the many examples employed in the text. The book is comprehensive, well written, and will surely be regarded as a standard text in both astrostatistics and physical statistics.Joseph M. Hilbe, President, International Astrostatistics Association, Professor Emeritus, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University