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The Development of Bayesian Statistics

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Journal of the Indian Institute of Science Aims and scope

Abstract

The incorporation of Bayesian inference into practical statistics has seen many changes over the past century, including hierarchical and nonparametric models, general computing tools that have allowed the routine use of nonconjugate distributions, and the incorporation of model checking and validation in an iterative process of data analysis. We discuss these and other technical advances along with parallel developments in philosophy, moving beyond traditional subjectivist and objectivist frameworks to ideas based on prediction and falsification. Bayesian statistics is a flexible and powerful approach to applied statistics and an imperfect but valuable way of understanding statistics more generally.

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Correspondence to Andrew Gelman.

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For the Journal of the Indian Institute of Science. We thank the U.S. Office of Naval Research for partial support of this work.

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Gelman, A. The Development of Bayesian Statistics. J Indian Inst Sci 102, 1131–1134 (2022). https://doi.org/10.1007/s41745-022-00307-y

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  • DOI: https://doi.org/10.1007/s41745-022-00307-y

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