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.
Bayesian Core: A Practical Approach to Computational Bayesian Statistics (Springer Texts in Statistics)
📄 Viewing lite version
Full site ›
Book Details
Author(s)Jean-Michel Marin, Christian Robert
PublisherSpringer
ISBN / ASIN1441922865
ISBN-139781441922861
AvailabilityUsually ships in 3 to 5 weeks
Sales Rank2,667,029
CategoryMathematics
MarketplaceUnited States 🇺🇸
Description ▲
More Books in Mathematics
Collins Primary Maths: Year 1 Bk.2
View
Collins Primary Maths: Year 2 Bk.2
View
Maths Plus: Bk.2
View
Spark Island: KS2 National Tests Maths
View
KS3 Maths (Test Practice)
View
Pupil Book 3B (Collins New Primary Maths)
View
Collins New Primary Maths – Pupil Book 5C
View
Year 9 Pupil Book 3 (Levels 6-8) (New Maths Frameworki…
View
Student Book Foundation 1: Foundation 1: Edexcel Modul…
View