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The MADAI collaboration (Models and Data Analysis Initiative) is devoted to developing statistical analysis and visualization tools for the purpose of comparing complex models and simulations to large scale heterogenous data sets. Since many of the challenges cross a multitude of disciplines, MADAI's analysis infrastructure will be designed to simultaneously address several pressing scientific challenges, and once finished, should be extensible to innumerable other problems.

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MADAI HOME | madai.msu.edu Reviews

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The MADAI collaboration (Models and Data Analysis Initiative) is devoted to developing statistical analysis and visualization tools for the purpose of comparing complex models and simulations to large scale heterogenous data sets. Since many of the challenges cross a multitude of disciplines, MADAI's analysis infrastructure will be designed to simultaneously address several pressing scientific challenges, and once finished, should be extensible to innumerable other problems.

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MADAI HOME | madai.msu.edu Reviews

https://madai.msu.edu

The MADAI collaboration (Models and Data Analysis Initiative) is devoted to developing statistical analysis and visualization tools for the purpose of comparing complex models and simulations to large scale heterogenous data sets. Since many of the challenges cross a multitude of disciplines, MADAI's analysis infrastructure will be designed to simultaneously address several pressing scientific challenges, and once finished, should be extensible to innumerable other problems.

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madai.msu.edu

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MADAI Members

http://madai.msu.edu/members.html

Scott Pratt (Principal Investigator). Professor, Theoretical Nuclear Physics. Department of Physics and Astronomy and National Superconducting Cyclotron Laboratory. Michigan State University, East Lansing, MI 48824. 517) 908-7460, prattsc at msu.edu. Associate Professor, Theoretical Nuclear Physics. Duke University, Durham, NC 27708. 919) 660-2479, bass at phy.duke.edu. University Distinguished Professor, Theoretical Nuclear Physics. Michigan State University, East Lansing, MI 48824. Michigan State Unive...

2

MADAI NEWS

http://madai.msu.edu/news.html

Several members of the relativistic heavy ion modeling group will attending the CATHIE/TECHQM meeting at Brookhaven from Dec. 13-18. The meeting will have a session devoted to creating a working group whose purpose will be to package data and models in a format that permits sophisticated and rigorous statistical analysis. This should prove invaluable to the MADAI effort. The first MADAI collaboration meeting will take place at SANDIA National Laboratory, May 11-14. (Agenda and information).

3

MADAI Visualization

http://madai.msu.edu/visualization.html

Visualization plays a central role in the MADAI effort. First, a toolset is being designed to assist modelers in observing the differential effects of changes in parameters and the differences in changing assumptions. This will enable the modelers to gain a better feel for which observables might provide the best leverage for determining fundamental parameters or for best understanding the consequences and manifestations of model choices and assumptions.

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MADAI HOME

http://madai.msu.edu/index.html

The MADAI collaboration (Models and Data Analysis Initiative) is devoted to developing statistical analysis and visualization tools for the purpose of comparing complex models and simulations to large scale heterogenous data sets. Since many of the challenges cross a multitude of disciplines, MADAI's analysis infrastructure will be designed to simultaneously address several pressing scientific challenges, and once finished, should be extensible to innumerable other problems.

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MADAI STATS

http://madai.msu.edu/stats.html

MADAI will build a tool set that can not only statistically address the modeling projects or its members, but should be extensible to numerous other problems. Tools will include routines for calculating the likelihood, tools for tuning the emulator, and for MCMC search procedures.

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MADAI HOME

The MADAI collaboration (Models and Data Analysis Initiative) is devoted to developing statistical analysis and visualization tools for the purpose of comparing complex models and simulations to large scale heterogenous data sets. Since many of the challenges cross a multitude of disciplines, MADAI's analysis infrastructure will be designed to simultaneously address several pressing scientific challenges, and once finished, should be extensible to innumerable other problems.

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