Format:
1 Online-Ressource (XVII, 593 Seiten)
Edition:
Second edition
ISBN:
9780429639142
,
9780429029608
Series Statement:
Chapman & Hall/CRC texts in statistical science
Content:
Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This unique computational approach ensures that you understand enough of the details to make reasonable choices and interpretations in your own modeling work. The text presents causal inference and generalized linear multilevel models from a simple Bayesian perspective that builds on information theory and maximum entropy. The core material ranges from the basics of regression to advanced multilevel models. It also presents measurement error, missing data, and Gaussian process models for spatial and phylogenetic confounding. The second edition emphasizes the directed acyclic graph (DAG) approach to causal inference, integrating DAGs into many examples. The new edition also contains new material on the design of prior distributions, splines, ordered categorical predictors, social relations models, cross-validation, importance sampling, instrumental variables, and Hamiltonian Monte Carlo. It ends with an entirely new chapter that goes beyond generalized linear modeling, showing how domain-specific scientific models can be built into statistical analyses.
Additional Edition:
ISBN 9780367139919
Additional Edition:
Erscheint auch als Druck-Ausgabe McElreath, Richard, 1973 - Statistical rethinking Boca Raton : CRC Press, 2020 ISBN 9780367139919
Additional Edition:
ISBN 036713991X
Language:
English
Subjects:
Mathematics
,
Psychology
Keywords:
Bayes-Entscheidungstheorie
;
R
;
Statistisches Modell
URL:
https://ebookcentral.proquest.com/lib/kxp/detail.action?docID=6133700
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