Another beta release of the OpenMx 1.1 series is available for download. Use the alternate installation command in an R terminal source("https://openmx.ssri.psu.edu/getNewOpenMx.R").

It contains the following changes from the last OpenMx 1.1 Beta Release:

This release contains the following changes from 1.0.6:

• error checking in front-end for non-positive-definite observed covariance matrices
• fixed a bug in MxMatrix indexing operator
• added deprecation warning for argument 'all'=TRUE in mxPath(). For more information on the deprecation see: https://openmx.ssri.psu.edu/wiki/deprecation-mxpathall-true-argument

A more stable beta release of the OpenMx 1.1 series is available for download. Use the alternate installation command in an R terminal source("https://openmx.ssri.psu.edu/getNewOpenMx.R").

For more information on OpenMx 1.1 please see our original announcement.

Below is the full change log since the OpenMx 1.0.0 release. We have made numerous small improvements and bug fixes.

The beta release of the OpenMx 1.1 series is available for download. Use the alternate installation command in an R terminal source("https://openmx.ssri.psu.edu/getNewOpenMx.R"). The new series of OpenMx is the result of nearly 8 months of development and much feedback from the user community.

In the OpenMx 1.0.x series, when a RAM model with raw data is fitted, the resulting model that is returned by mxRun() has a FIML objective function instead of a RAM objective function. This transformation was performed for convenience, it allowed us to support RAM models with raw data by using our existing implementation for FIML optimization. However it has been a source of confusion (rightly so) as new paths cannot be added or eliminated from the resulting fitted model.

We are pleased to announce the second release in our OpenMx pre-release series. As we develop new features for OpenMx, we will periodically make pre-releases available that contain the new functionality. The latest pre-release can be downloaded using the following installation url. You will notice that the pre-releases will always have the version number 999. You can find the true version number by looking at the last four digits of mxVersion() after the "999.0.0-".

Quick turnaround on this release. It fixes a bug that would throw an error message at the beginning of execution when mxRun() was called. This bug affected models that had multiple data sets, and contained definition variables, and contained at least one data set with no definition variables.

The latest release of the OpenMx 1.0 series. Small bug fixes and other code cleanup.

Changes:

• added error checking in ML objective to match expected covariance and observed covariance matrices
• updated BootstrapParallel.R demo to use mxData() instead of model@data
• added the dataset from the Psychometrika article (www.springerlink.com/content/dg37445107026711)

This release fixes several bugs in the 1.0 stable series of OpenMx.

Changes:

• added initialization to load OpenMx on swift workers

• only calculating CIs for upper triangle on symmetric matrices
• fix bug with very large number of omxUntitledName() objects
• incorporated NaN unsafe matrix-vector multiplication (dgemv) from R <= 2.11.1
• fix bug in mxModel() when using remove = TRUE
• added intervals to MxModel class documentation