The Bayesian analysis software developed at Washington University

Karen R. Marutyan, G. Larry Bretthorst

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Over the last few years there has been an ongoing effort at the Biomedical Magnetic Resonance Laboratory within Washington University to develop data analysis applications using Bayesian probability theory. A few of these applications are specific to Magnetic Resonance data, however, most are general and can analyze data from a wide variety of sources. These data analysis applications are server based and they have been written in such a way as to allow them to utilize as many processors as are available. The interface to these Bayesian applications is a client based Java interface. The client, usually a Windows PC, runs the interface, sets up an analysis, sends the analysis to the server, fetches the results and displays the appropriate plots on the users client machine. Together, the client and server software can be used to solve a host of interesting problems that occur regularly in the sciences. In this paper, we describe both the client and server software and briefly discuss how to acquire, install and maintain this software.

Original languageEnglish
Title of host publicationBayesian Inference and Maximum Entropy Methods in Science and Engineering - 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Pages368-381
Number of pages14
DOIs
StatePublished - 2009
Event29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering - Oxford, MS, United States
Duration: Jul 5 2009Jul 10 2009

Publication series

NameAIP Conference Proceedings
Volume1193
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering
CountryUnited States
CityOxford, MS
Period07/5/0907/10/09

Keywords

  • Bayesian analysis software
  • Bayesian probability theory
  • Markov chain Monte Carlo

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