mxSave | R Documentation |
The function saves the last state of a model to a checkpoint file.
mxSave(model, chkpt.directory = ".", chkpt.prefix = "")
model |
an MxModel object |
chkpt.directory |
character. Directory where the checkpoint file is located |
chkpt.prefix |
character. Prefix of the checkpoint file |
In general, the arguments ‘chkpt.directory’ and ‘chkpt.prefix’ should be identical to the mxOption
: ‘Checkpoint Directory’ and ‘Checkpoint Prefix’ that were specified on the model before execution.
Alternatively, the checkpoint file can be manually loaded as a data.frame in R. Use read.table
with the options header=TRUE, sep="\t", stringsAsFactors=FALSE, check.names=FALSE
.
Returns a logical indicating the success of writing the checkpoint file to the checkpoint directory.
The OpenMx User's guide can be found at https://openmx.ssri.psu.edu/documentation
Other model state:
mxComputeCheckpoint()
,
mxRestore()
library(OpenMx)
# Simulate some data
x=rnorm(1000, mean=0, sd=1)
y= 0.5*x + rnorm(1000, mean=0, sd=1)
tmpFrame <- data.frame(x, y)
tmpNames <- names(tmpFrame)
dir <- tempdir() # safe place to create files
mxOption(key="Checkpoint Directory", value=dir)
# Create a model that includes an expected covariance matrix,
# an expectation function, a fit function, and an observed covariance matrix
data <- mxData(cov(tmpFrame), type="cov", numObs = 1000)
expCov <- mxMatrix(type="Symm", nrow=2, ncol=2, values=c(.2,.1,.2), free=TRUE, name="expCov")
expFunction <- mxExpectationNormal(covariance="expCov", dimnames=tmpNames)
fitFunction <- mxFitFunctionML()
testModel <- mxModel(model="testModel", expCov, data, expFunction, fitFunction)
#Use mxRun to optimize the free parameters in the expected covariance matrix
modelOut <- mxRun(testModel)
modelOut$expCov
# Save the ending state of modelOut in a checkpoint file
mxSave(modelOut)
# Restore the saved model from the checkpoint file
modelSaved <- mxRestore(testModel)
modelSaved$expCov
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