Bayesian statistics and modelling

Rens van de Schoot; Sarah A. Depaoli; Ruth King; Bianca M. R. Kramer; Kaspar Märtens; Mahlet G. Tadesse; Marina Vannucci; Andrew Gelman; Duco Veen; Joukje E. Willemsen; Christopher Yau

doi:10.1038/s43586-020-00001-2

Bayesian statistics and modelling

Rens van de Schoot (Utrecht University) iD Sarah A. Depaoli (University of California, Merced) iD Ruth King (The Alan Turing Institute) iD Bianca M. R. Kramer (Utrecht University) iD Kaspar Märtens (University of Oxford) iD Mahlet G. Tadesse (Georgetown University) iD Marina Vannucci (Rice University) iD Andrew Gelman (Columbia University) iD Duco Veen (Utrecht University) iD Joukje E. Willemsen (Utrecht University) iD Christopher Yau (University of Manchester) iD

Journal: Nature Reviews Methods Primers • 2021-01-14 • Nature Portfolio • ISSN: 2662-8449

Abstract

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Subjects & Keywords

# Statistical Methods and Bayesian Inference # Mathematics # Markov Chains and Monte Carlo Methods # Bayesian Modeling and Causal Inference # Computer Science

How to Cite this Article

                    Rens van de Schoot, Sarah A. Depaoli, Ruth King, et al. (2021). "Bayesian statistics and modelling". Nature Reviews Methods Primers. https://doi.org/10.1038/s43586-020-00001-2                

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Identifiers & Provenance

DOI: https://doi.org/10.1038/s43586-020-00001-2 ↗
OpenAlex: W3128782210 ↗
Primary Index: OPENALEX