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Applied Bayesian Modelling
Abstract
This book provides an accessible approach to Bayesian computing and data analysis, with an emphasis on the interpretation of real data sets. Following in the tradition of the successful first edition, this book aims to make a wide range of statistical modeling applications accessible using tested code that can be readily adapted to the reader's own applications. The second edition has been thoroughly reworked and updated to take account of advances in the field. A new set of worked examples is included. The novel aspect of the first edition was the coverage of statistical modeling using WinBU
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Cited by
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Nakagawa, S., & Santos, E. S. A. (2012) · Evolutionary Ecology · doi:10.1007/s10682-012-9555-5 · Cited by 1,032
Assessing Evidence Inconsistency in Mixed Treatment Comparisons
Lu, G., & Ades, A. E. (2006) · Journal of the American Statistical Association · doi:10.1198/016214505000001302 · Cited by 756
Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method
Wagenmakers, E.-J., Lodewyckx, T., Kuriyal, H., & Grasman, R. (2010) · Cognitive Psychology · doi:10.1016/j.cogpsych.2009.12.001 · Cited by 740
State Repression and the Domestic Democratic Peace
Davenport, C. (2007) · doi:10.1017/cbo9780511510021 · Cited by 549
Metadata
- Authors
- Congdon, P.
- Venue
- Wiley Series in Probability and Statistics
- Publisher
- Wiley
- Published
- 2003-03-11
- ISSN
- 1940-6347 (ISSN-L)
- OpenAlex
- W1567548236
- Cited by
- 653
- References
- 0
- FWCI
- 9.42
- Type
- book
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
