mxFIMLObjective {OpenMx}R Documentation

Function To Create MxFIMLObjective Object


This function creates a new MxFIMLObjective object.


mxFIMLObjective(covariance, means)


covariance A character string indicating the name of the expected covariance algebra.
means An character string indicating the name of expected means algebra.


Objective functions are functions for which free parameter values are chosen such that the value of the objective function is minimized. The mxFIMLObjective function uses full-information maximum likelihood to provide maximum likelihood estimates of free parameters in the algebra defined by the 'covariance' and 'means' arguments. The 'covariance' argument takes an MxAlgebra object, which defines the expected covariance of an associated MxData object. The 'means' argument takes an MxAlgebra object, which defines the expected means of an associated MxData object.

mxFIMLObjective evaluates with respect to an MxData object. The MxData object need not be referenced in the mxFIMLObjective function, but must be included in the MxModel object. mxFIMLObjective requires that the 'type' argument in the associated MxData object be equal to 'raw'. Missing values are permitted in the associated MxData object.

To evaluate, place MxFIMLObjective objects, the mxData object for which the expected covariance approximates, referenced MxAlgebra and MxMatrix objects, and optional MxBounds and MxConstraint objects in an MxModel object. This model may then be evaluated using the mxRun function. The results of the optimization can be found in the 'output' slot of the resulting model, and may be referenced using the Extract functionality.


Returns a new MxFIMLObjective object. MxFIMLObjective objects should be included with models with referenced MxAlgebra, MxData and MxMatrix objects.


The OpenMx User's guide can be found at


A <- mxMatrix(values = 0.5, nrow = 2, ncol = 1, 
        free = TRUE, name = "A")

D <- mxMatrix(type = "Diag", values = c(0, 0.5), 
        free = c(FALSE, TRUE), nrow = 2, name = "D")
M <- mxMatrix(type = "Zero", nrow = 1, ncol = 2, name = "M")

expectedCov <- mxAlgebra(A %*% t(A) + D, "expectedCov")

objective <- mxFIMLObjective("expectedCov", "M")

model <- mxModel(A, D, expectedCov, objective)

[Package OpenMx version 0.1-1 Index]