A 250-year argument: Belief, behavior, and the bootstrap

By Bradley Efron. 2012

51 citations recorded by the source corpus.

The year 2013 marks the 250th anniversary of Bayes rule, one of the two fundamental inferential principles of mathematical statistics. The rule has been influential over the entire period—and controversial over most of it. Its reliance on prior beliefs has been challenged by frequentism, which focuses instead on the behavior of specific estimates and tests under repeated use. Twentieth-century statistics was overwhelmingly behavioristic, especially in applications, but the twenty-first century has seen a resurgence of Bayesianism. Some simple examples are used to show what’s at stake in the argument. The bootstrap, a computer-intensive inference machine, helps connect Bayesian and frequentist practice, leading finally to an empirical Bayes example of collaboration between the two philosophies.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e28f032885e290495facb5aea8308f3ff8234406

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Statistics and Probability

Citations in the corpus

On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation (2020, methodology): “At the crossroad between the Bayesian and the frequentist approaches, the Bootstrap algo-rithm may provide a simple way to approximate the sampling distribution of an estimator, see e.g. [Efr12a, Efr12b].”