OpenMx version 2.7.11 is now available through CRAN and through our virginia.edu repository. Users running R version 3.4 under Mac OS X 10.11 "El Capitan" are advised to follow our website's instructions for installing OpenMx, since the CRAN build of the package still does not work with that combination of R and MacOS versions.
OpenMx now has a nonparametric bootstrapping feature! The re-sampling and refitting of the model is carried out in the compiled "backend," which is considerably faster than doing so in interpreted R code. OpenMx can provide bootstrap standard errors, quantile confidence intervals, and bias-corrected quantile confidence intervals, both for free parameters and for functions of free parameters (e.g., elements of MxAlgebras). For details, see the documentation for Several documentation pages have been edited for clarity.
Oakes standard errors (which are used with MxComputeEM compute steps) now work properly.
It is now possible to provide a repeated-sampling covariance matrix (of the free parameters) to Instances where SLSQP fails to move from its start values should now be rarer.
Peak memory demand of the GREML fitfunction and expectation should be lower, especially in cases where the dataset contains missing values.
New features, performance improvements, and bug-fixes in OpenMx v2.7.11 include the following:
mxBootstrap(), mxComputeBootstrap(), mxBootstrapEval(), and mxBootstrapEvalByName().
mxSE() and mxStandardizeRAMpaths() (which by default calculate such a matrix from the Hessian in the model's output slot). This makes it possible to use a robust or bootstrap covariance matrix with those functions.