OpenMx: Multipurpose Software for Statistical Modeling

If you are looking for the  OpenMx homepage, but have landed here, go to  http://openmx.psyc.virginia.edu.

Contents

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Aims

The OpenMx Project intends to rewrite and extend the popular statistical package  Mx to address the challenges facing a large range of modern statistical problems such as:

  • The difficulty of measuring behavioral traits
  • The availability of technologies - such as such as magnetic resonance imaging, continuous physiological monitoring and microarrays - which generate extremely large amounts of data often with complex time-dependent patterning, and
  • Increased sophistication in the statistical models used to analyze the data.

To address these problems, the Mx Structural Equation Modeling software will be rewritten so as to:

  • Split OpenMx into modules that interoperate with the R statistical package,
  • Release OpenMx as open source so as to provide a stable path for future maintenance and development, and
  • Integrate OpenMx with the  Swift (formerly VDL) parallel workflow software.

Grid/parallel computing and data management using Swift will provide significant speedup for processing large (up to multi-terabyte) data sets, through the use of analytical workflows that provide detailed provenance tracking and annotation of derived results. Revised algorithms for model fitting and optimization will increase both the scope of the software and its performance. Both the code and its use will be documented and disseminated at national and international workshops.

This wiki is currently intended primarily for the software developers of Open Mx.