mxRestore {OpenMx} | R Documentation |
The function loads the last saved state from a checkpoint file.
mxRestore(model, chkpt.directory = ".", chkpt.prefix = "")
model |
MxModel object to be loaded. |
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 specificed 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’, ‘stringsAsFactors=FALSE’ and ‘check.names=FALSE’.
Returns an MxModel object with free parameters updated to the last saved values.
The OpenMx User's guide can be found at http://openmx.psyc.virginia.edu/documentation.
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) # 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, checkpoint = TRUE) modelOut$expCov #Use mxRestore to load the last checkpoint saved state of the model modelRestore <- mxRestore(testModel) modelRestore$expCov