TY - GEN
T1 - The Bayesian analysis software developed at Washington University
AU - Marutyan, Karen R.
AU - Bretthorst, G. Larry
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Bayesian analysis software
KW - Bayesian probability theory
KW - Markov chain Monte Carlo
UR - http://www.scopus.com/inward/record.url?scp=72949101291&partnerID=8YFLogxK
U2 - 10.1063/1.3275636
DO - 10.1063/1.3275636
M3 - Conference contribution
AN - SCOPUS:72949101291
SN - 9780735407299
T3 - AIP Conference Proceedings
SP - 368
EP - 381
BT - Bayesian Inference and Maximum Entropy Methods in Science and Engineering - 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering
Y2 - 5 July 2009 through 10 July 2009
ER -