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1995•Unpublished venueRequires access

Bayesian Data Analysis

Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin

Open publisher page 13,733 citations

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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What this paper is about

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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OpenAlex reports 13733 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available 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

Key concepts: Variable-order Bayesian network, Approximate Bayesian computation, Computer science, Markov chain Monte Carlo, Bayesian inference, Bayesian probability, Inference, Dirichlet process

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