First OpenMx 2.0 beta is released

We are pleased to announce that the first beta of OpenMx version 2.0 is now publicly available! Interested users can download and install this new version by copy-pasting source('https://openmx.ssri.psu.edu/getOpenMxBeta.R') into the R command line and pressing 'Return'. The OpenMx User Guide for the beta is attached to this announcement.

This initial beta release has a number of exciting new features, which include the following:

• CSOLNP, a new, open-source numerical optimizer written in C++.
• Split between a model's expectation (how it's specified) and its fit (its objective function to be minimized).
• LISREL specification of models.
• State-space modeling.
• Analytic derivatives of the objective function, which can be provided by the user as mxAlgebras.
• mxThreshold(), a new function which enables a smoother interface for setting up analyses of ordinal data.
• Compatibility with the latest version of R (v3.1.0).
• mxFitFunctionMultigroup(), a new function which enables a smoother interface for setting up multi-group analyses.
• mxCompute sequences, which can tell the program what to calculate and how to do so when running an mxModel.
• Replacement of @ accessors with $ accessors in mxModel objects. You no longer have to keep track of when to use which; just always use $!

NOTE: Concerning the last bullet point, users should definitely get into the habit of ALWAYS using $ instead of @. For example, myModelRun@output$estimate would now be myModelRun$output$estimate. We CANNOT guarantee that every usage of the @ accessor that worked with versions 1.3/1.4 will continue to work in 2.0.

Users are advised that this initial beta release of OpenMx 2.0 also has a few known issues:

• This beta does not presently have an updated log of changes, so experienced users won't yet be able to get a quick summary of "what's different" by looking at the release notes (such as appear in Chapter 5 of the User Guide).
• CSOLNP has a known memory leak, which sometimes causes R to repeatedly allocate memory until it cannot do so anymore, which usually results in R crashing. CSOLNP is the default optimizer for the beta. However, the mxOption() function can be used to switch to using NPSOL if necessary.
• CSOLNP can return inaccurate parameter estimates sometimes, too. Users should use NPSOL to verify results obtained with CSOLNP before trusting them!

We are eager to receive user feedback about this beta of OpenMx 2.0! Please post questions, comments, and issues to the OpenMx Forums.