OpenMx version 2.7.10 is now available through CRAN.
New features, performance improvements, and bug-fixes in OpenMx v2.7.10 include the following:
- OpenMx is now able to check the first-order optimality conditions for solutions obtained by SLSQP when MxConstraints are involved. Note that SLSQP therefore may now warn about status code 6 in cases where formerly it did not.
- Expectation-maximization has been made more generic.
- A new function usable in MxAlgebras,
mxRobustLog(), has been implemented.mxRobustLog()returns the natural logarithm of its argument, unless the argument is zero, in which case it returns -745 instead of-Inf(see documentation for details). It is recommended for use with mixture models. - Another new function usable in MxAlgebras,
mxEvaluateOnGrid(), has been implemented. It is useful for quadrature integration. - The way the WLS fitfunction handles MxConstraints has been improved.
- When using the WLS fitfunction, OpenMx will not attempt to calculate a chi-square statistic when no standard errors are available.
omxParallelCI()now respects locally set mxOptions, and no longer unnecessarily redoes the primary optimization (for point estimates).- Previously,
mxGetExpected()could fail in cases where one MxModel references a component of another MxModel, when both are submodels inside a "container" MxModel. This bug has been repaired. mxGetExpected()now works with GREML expectation.mxGetExpected()can now provide asymptotic ("infinite-time") covariance matrices for state-space expectations.mxSE()now safely handles MxConstraints.- The Nelder-Mead optimizer's default method for handling equality MxConstraints is now the newly implemented "GDsearch" method, which uses SLSQP as a subsidiary optimizer.
mxTryHard()now works with MxModels that use the Nelder-Mead optimizer.mxCompare()now behaves more sensibly when it is comparing MxModels that have the same degrees-of-freedom.- A bug involving
mxRefModels()when using WLS with a multigroup MxModel has been repaired. mxAutoStart()now works better with multigroup models. Mac users of R v3.4 can download a "bleeding edge" developers' build of OpenMx from here, but note that the bleeding edge build is not a stable package release and is only minimally tested. Furthermore, it does not work on Mac OS X 10.11 "El Capitan."