Bayesian Analysis is an electronic journal of the International Society for Bayesian Analysis. It seeks to publish a wide range of articles that demonstrate or discuss Bayesian methods in some theoretical or applied context. The journal welcomes submissions involving presentation of new computational and statistical methods; critical reviews and discussions of existing approaches; historical perspectives; description of important scientific or policy application areas; case studies; and methods for experimental design, data collection, data sharing, or data mining.

Evaluation of submissions is based on importance of content and effectiveness of communication. Discussion papers are typically chosen by the Editor in Chief, or suggested by an Editor, among the regular submissions. In addition, the Journal encourages individual authors to submit manuscripts for consideration as discussion papers.

Top downloads over the last seven days

Overall Objective PriorsJames O. Berger, Jose M. Bernardo, and Dongchu SunVolume 10, Number 1 ( 2015 )
A review of Bayesian variable selection methods: what, how and whichR. B. O'Hara and M. J. SillanpääVolume 4, Number 1 ( 2009 )
Sequential Monte Carlo with Adaptive Weights for Approximate Bayesian ComputationFernando V. Bonassi and Mike WestVolume 10, Number 1 ( 2015 )
RejoinderJames O. Berger, Jose M. Bernardo, and Dongchu SunVolume 10, Number 1 ( 2015 )
Comment on Article by Berger, Bernardo, and SunJudith RousseauVolume 10, Number 1 ( 2015 )
  • ISSN: 1936-0975 ( print ) , 1931-6690 ( electronic )
  • Publisher: International Society for Bayesian Analysis
  • Discipline(s): Statistics and Probability
  • Full text available in Euclid: 2006 --
  • Access: Open access
  • Euclid URL: ba