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.
Similar content being viewed by others
References
Box GEP (1980) Sampling and Bayes inference in scientific modelling and robustness. J R Stat Soc A 143:383–430
Efron B, Morris C (1972) Limiting the risk of Bayes and empirical Bayes estimators—Part II: The empirical Bayes case. J Am Stat Assoc 67:130–139
Gelman A, Vehtari A, Simpson D, Margossian CC, Carpenter B, Yao Y, Bürkner PC, Kennedy L, Gabry J, Modrák M (2021) Bayesian workflow. https://arxiv.org/abs/2011.01808
Lindley DV, Smith AFM (1972) Bayes estimates for the linear model. J R Stat Soc B 34:1–41
Little RJA (1993) Post-stratification: a modeler’s perspective. J Am Stat Assoc 88:1001–1012
Pearson K (1916) Mathematical contributions to the theory of evolution, XIX: Second supplement to a memoir on skew variation. Philos Trans R Soc A 216:429–457
Rubin DB (1984) Bayesianly justifiable and relevant frequency calculations for the applied statistician. Ann Stat 12:1151–1172
Stigler SM (1986) The History of Statistics. Harvard University Press, Cambridge
Tukey JW (1977) Exploratory data analysis. Addison-Wesley, Reading
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
For the Journal of the Indian Institute of Science. We thank the U.S. Office of Naval Research for partial support of this work.
Rights and permissions
About this article
Cite this article
Gelman, A. The Development of Bayesian Statistics. J Indian Inst Sci 102, 1131–1134 (2022). https://doi.org/10.1007/s41745-022-00307-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41745-022-00307-y