Marin / Robert Bayesian Core: A Practical Approach to Computational Bayesian Statistics

1. Auflage 2007
ISBN: 978-0-387-38983-7
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 272 Seiten, eBook

Reihe: Springer Texts in Statistics

After that, it was down to attitude. —Ian Rankin, Black & Blue. — The purpose of this book is to provide a self-contained (we insist!) entry into practical and computational Bayesian statistics using generic examples from the most common models for a class duration of about seven blocks that roughly correspond to 13 to 15 weeks of teaching (with three hours of lectures per week), depending on the intended level and the prerequisites imposed on the students. (That estimate does not include practice—i. e. , programming labs—since those may have a variable duration, also depending on the s- dents’ involvement and their programming abilities. ) The emphasis on practice is a strong feature of this book in that its primary audience consists of gr- uate students who need to use (Bayesian) statistics as a tool to analyze their experiments and/or datasets. The book should also appeal to scientists in all ?elds, given the versatility of the Bayesian tools. It can also be used for a more classical statistics audience when aimed at teaching a quick entry to Bayesian statistics at the end of an undergraduate program for instance. (Obviously, it can supplement another textbook on data analysis at the graduate level.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Marin, Jean-Michel

Robert, Christian

Inhaltsverzeichnis

User’s Manual.- Normal Models.- Regression and Variable Selection.- Generalized Linear Models.- Capture–Recapture Experiments.- Mixture Models.- Dynamic Models.- Image Analysis.