UID:
almahu_9949385465802882
Umfang:
1 online resource :
,
illustrations (some color).
ISBN:
9781003019169
,
1003019161
,
9781000520040
,
1000520048
,
1000520072
,
9781000520071
Serie:
Chapman & Hall/CRC texts in statistical science series
Inhalt:
"Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying mathematical theory. The book starts with a refresher of the Bayesian Inference concepts. The second chapter introduces modern methods for Exploratory Analysis of Bayesian Models. With an understanding of these two fundamentals the subsequent chapters talk through various models including linear regressions, splines, time series, Bayesian additive regression trees. The final chapters include Approximate Bayesian Computation, end to end case studies showing how to apply Bayesian modelling in different settings, and a chapter about the internals of probabilistic programming languages. Finally the last chapter serves as a reference for the rest of the book by getting closer into mathematical aspects or by extending the discussion of certain topics. This book is written by contributors of PyMC3, ArviZ, Bambi, and Tensorflow Probability among other libraries"--
Anmerkung:
ForewordPrefaceSymbolsChapter 1 Bayesian InferenceChapter 2 Exploratory Analysis of Bayesian ModelsChapter 3 Linear Models and Probabilistic Programming LanguagesChapter 4 Extending Linear ModelsChapter 5 SplinesChapter 6 Time SeriesChapter 7 Bayesian Additive Regression TreesChapter 8 Approximate Bayesian ComputationChapter 9End to End Bayesian WorkflowsChapter 10 Probabilistic Programming LanguagesChapter 11 Appendiceal TopicsGlossaryBibliographyIndex
Weitere Ausg.:
Print version: Martin, Osvaldo. Bayesian modeling and computation in Python Boca Raton : CRC Press, 2022 ISBN 9780367894368
Sprache:
Englisch
Schlagwort(e):
Electronic books.
URL:
https://www.taylorfrancis.com/books/9781003019169
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