Bayesian Core: A Practical Approach to Computational Bayesian Statistics

1. Auflage 2007. Corr. 2. printing. Softcover version of original hardcover Auflage 2007
ISBN: 978-1-4419-2286-1
Verlag: Springer Netherlands

Buch, Englisch, 258 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 421 g

Reihe: Springer Texts in Statistics

This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on standard statistical models and backed up by discussed real datasets available from the book website, it provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Marin, Jean-Michel

Robert, Christian

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Inhaltsverzeichnis

User's manual.- Normal models.- Regression and variable selection.- Generalised linear models.- Capture-recapture experiments.- Mixture models.- Dynamic models.- Image analysis.