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 #  AuthorTitleAccn#YearItem Type Claims
1 Joseph M. Hilbe Bayesian models for astrophysical data: Using R, JAGS, Python, and Stan 026263 2017 Book  
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TitleBayesian models for astrophysical data: Using R, JAGS, Python, and Stan
Author(s)Joseph M. Hilbe;Rafael S. de Souza;Emille E. O. Ishida
PublicationUk, Cambridge University Press, 2017.
Descriptionxvii, 393p
Abstract NoteThis comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally.
ISBN,Price9781107133082 : 60.00
Classification519.226:52
Keyword(s)1. ASTRONOMY-DATA PROCESSING 2. ASTROPHYSICAL DATA PROCESSING 3. BAYESIAN MODELS 4. JAGS-ASTROPHYSICAL DATA PROCESSING 5. PYTHON-ASTROPHYSICAL DATA PROCESSING 6. R-ASTROPHYSICAL DATA PROCESSING 7. STAN-ASTROPHYSICAL DATA PROCESSING 8. STATISTICAL ASTRONOMY 9. STATISTICAL DATA PROCESSING
Item TypeBook

Circulation Data
Accession#  Call#StatusIssued ToReturn Due On Physical Location
026263   519.226:52/HIL/026263  Issued DS13: Sourav Das 17/Jul/2024

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