mxOption {OpenMx}R Documentation

Set or Clear an Optimizer Option


The function sets, shows, or clears an option that is specific to the optimizer in the back-end.


mxOption(model, key, value, reset = FALSE)



An MxModel object or NULL


The name of the option.


The value of the option.


If TRUE then reset all options to their defaults.


mxOption is used to set, clear, or query an option (given in the ‘key’ argument) in the back-end optimizer. Valid option keys are listed below.

Use value = NULL to remove an existing option. Leaving value blank will return the current value of the option specified by ‘key’.

To reset all options to their default values, use ‘reset = TRUE’. When reset = TRUE, ‘key’ and ‘value’ are ignored.

If the ‘model’ argument is set to NULL, the default optimizer option (i.e those applying to all models by default) will be set.

To see the defaults, use getOption('mxOptions').

Before the model is submitted to the back-end, all keys and values are converted into strings using the as.character function.

The maximum number of major iterations (the option “Major iterations”) for optimization for NPSOL can be specified either by using a numeric value (such as 50, 1000, etc) or by specifying a user-defined function. The user-defined function should accept two arguments as input, the number of parameters and the number of constraints, and return a numeric value as output.

OpenMx options

Number of Threads i the number of processor cores to use. Use detectCores() to find how many are available.
Calculate Hessian [Yes | No] calculate the Hessian explicitly after optimization.
Standard Errors [Yes | No] return standard error estimates from the explicitly calculate hessian.
Default optimizer [NPSOL | SLSQP | CSOLNP] the gradient-descent optimizer to use
Number of Threads [0|1|2|...|10|...] number of threads used for optimization. This is how parallelism works. Default value of 0 uses detectCores() - 1.
Feasibility tolerance r the maximum acceptable absolute violations in linear and nonlinear constraints.
Optimality tolerance r the maximum acceptable difference in fit.
Gradient algorithm see list finite difference method, either 'forward' or 'central'.
Gradient iterations 1:4 the number of Richardson extrapolation iterations

NPSOL-specific options

Nolist this option suppresses printing of the options
Print level i the value of i controls the amount of printout produced by the major iterations
Minor print level i the value of i controls the amount of printout produced by the minor iterations
Print file i for i > 0 a full log is sent to the file with logical unit number i.
Summary file i for i > 0 a brief log will be output to file i.
Function precision r a measure of accuracy with which f and c can be computed.
Infinite bound size r if r > 0 defines the "infinite" bound bigbnd.
Major iterations i or a function the maximum number of major iterations before termination.
Verify level [-1:3 | Yes | No] see NPSOL manual.
Line search tolerance r controls the accuracy with which a step is taken.
Derivative level [0-3] see NPSOL manual.
Hessian [Yes | No] return the Hessian (Yes) or the transformed Hessian (No).

Checkpointing options

Always Checkpoint [Yes | No] whether to checkpoint all models during optimization.
Checkpoint Directory path the directory into which checkpoint files are written.
Checkpoint Prefix string the string prefix to add to all checkpoint filenames.
Checkpoint Fullpath path overrides the directory and prefix (useful to output to /dev/fd/2)
Checkpoint Units see list the type of units for checkpointing: 'minutes', 'iterations', or 'evaluations'.
Checkpoint Count i the number of units between checkpoint intervals.

Model transformation options

Error Checking [Yes | No] whether model consistency checks are performed in the OpenMx front-end
No Sort Data character vector of model names for which FIML data sorting is not performed
RAM Inverse Optimization [Yes | No] whether to enable solve(I - A) optimization
RAM Max Depth i the maximum depth to be used when solve(I - A) optimization is enabled

Multivariate normal integration parameters

mvnMaxPointsA i base number of integration points
mvnMaxPointsB i number of integration points per row
mvnMaxPointsC i number of integration points per rows^2
mvnAbsEps i absolute tolerance
mvnRelEps i relative tolerance


If a model is provided, it is returned with the optimizer option either set or cleared. If value is empty, the current value is returned.


The OpenMx User's guide can be found at

See Also

mxModel all uses of mxOption are via an mxModel whose options are set or cleared.


# set the Numbder of Threads (cores to use)
mxOption(NULL, "Number of Threads", detectCores() - 1)

testModel <- mxModel(model = "testModel") # make a model to use for example
testModel$options   # show the model options (none yet)
options()$mxOptions # list all mxOptions (global settings)

testModel <- mxOption(testModel, "Function precision", 1e-5) # set precision
testModel <- mxOption(testModel, "Function precision", NULL) # clear precision
# N.B. This is model-specific precision (defaults to global setting)

# may optimize for speed
# at cost of not getting standard errors
testModel <- mxOption(testModel, "Calculate Hessian", "No")
testModel <- mxOption(testModel, "Standard Errors"  , "No")

testModel$options # see the list of options you set

[Package OpenMx version 2.3.1 Index]