Cited by 260Statistical Methods and Bayesian InferenceMarkov Chains and Monte Carlo MethodsBayesian Modeling and Causal Inference

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Bayesian Data Analysis

Andrew Gelman, John B. Carlin, Hal S. Stern, Donald B. Rubin·1995·Routledge eBooks

DOI 10.4324/9780203491287

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Abstract

Bayesian Data Analysis describes how to conceptualize, perform, and critique statistical analyses from a Bayesian perspective. Using examples largely from the authors' own experiences, the book focuses on modern computational tools and obtains inferences using computer simulations. Its unique features include thorough discussions of the methods for

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Norris, D. O., Varona, L., Ng’ambi, J. W., Visser, D. P., Mbajiorgu, C. A., & Voordewind, S. F. (2010) · Livestock Science · doi:10.1016/j.livsci.2010.03.005 · Cited by 25

Authors: Gelman, A., Carlin, J. B., Stern, H. S., & Rubin, D. B.
Venue: Routledge eBooks
Publisher: Routledge
Published: 1995-06-01
DOI: 10.4324/9780203491287
OpenAlex: W4256118999
Cited by: 258
References: 0
Citations by year: 2025: 51 · 2024: 23 · 2023: 22 · 2022: 17 · 2021: 3 · 2020: 7 · 2019: 4 · 2018: 5 · 2017: 2 · 2016: 2 · 2015: 5 · 2014: 6 · 2013: 5 · 2012: 11
FWCI: 0.25
Type: book
Language: en
Open access: closed
Locations: Routledge eBooks (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
Keywords: Bayesian analysis, Bayesian inference, computational tools, computer simulation, statistical modeling, model criticism

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