| OpenMx {OpenMx} | R Documentation |
OpenMx is a package for structural equation modeling, matrix algebra optimization and other statistical estimation problems.
OpenMx solves algebra optimization and statistical estimation problems using matrix algebra. The OpenMx library defines a set of S4 classes and functions used to create them. The majority of these classes are used as arguments in models, which may include data, matrices, algebras, bounds and constraints. These models are then paired with either built-in objective functions (maximum likelihood and FIML) or user-defined functions. These models can then be optimized, resulting in parameter estimation, algebra evaluation, and output for additional models.
The main OpenMx functions are: mxAlgebra, mxBounds, mxCI, mxConstraint, mxData, mxMatrix, mxModel, and mxPath as well as mxAlgebraObjective, mxFIMLObjective, mxMLObjective and mxRAMObjective. These latter functions create the objectives for model estimation. Models are run (estimated) using mxRun.
These functions create the following Objects: MxModels, which can contain MxPaths, MxMatrix objects, and MxData as well as MxAlgebra, MxBounds, MxCIs (confidence intervals) and MxConstraints.
OpenMx comes with several useful datasets built-in. Access them using data(package="OpenMx")
The main learning material is online, but functions mxRun, mxModel, mxMatrix all have runnable examples to get you started.
The OpenMx User's guide can be found at http://openmx.psyc.virginia.edu/documentation.