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Bayesian computation: a statistical revolution.

Stephen P Brooks1

  • 1Statistical Laboratory, University of Cambridge, Centre for Mathematical Sciences, Wilberforce Road, Cambridge CB3 0WB, UK. steve@statslab.cam.ac.uk

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|December 12, 2003
PubMed
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Computing advances in the 1980s fueled a 1990s statistical revolution. This paper reviews statistical philosophies and the resurgence of Bayesian methods in modern practice.

Area of Science:

  • Statistics
  • Philosophy of Science
  • Computational Statistics

Background:

  • The 1990s witnessed a significant statistical revolution.
  • This revolution was driven by rapid advancements in computing technology starting in the early 1980s.
  • These technological leaps revived interest in long-standing statistical philosophies.

Purpose of the Study:

  • To review the historical and philosophical underpinnings of major statistical schools of thought.
  • To examine the implications of the resurgent Bayesian paradigm.
  • To assess the impact on current and future statistical practices.

Main Methods:

  • Historical review of statistical philosophies.
  • Philosophical analysis of statistical paradigms.

Related Experiment Videos

  • Examination of computational tools' influence on statistical practice.

    • Main Results:

    • The resurgence of the Bayesian paradigm is a key outcome.
    • Computational advancements have reshaped statistical methodologies.
    • A renewed focus on the philosophical foundations of statistics is evident.

    Conclusions:

    • The Bayesian paradigm's reascendance has profound implications for statistical practice.
    • Modern statistical practice is increasingly influenced by computational power.
    • Understanding the historical and philosophical context is crucial for future statistical developments.