| omxParallelCI {OpenMx} | R Documentation |
Create parallel models for parallel confidence intervals
omxParallelCI(model, run = TRUE)
model |
an MxModel with confidence intervals in it |
run |
whether to run the model or just return the parallelized interval models |
an MxModel object
require(OpenMx)
data(demoOneFactor)
manifests <- names(demoOneFactor)
latents <- c("G")
factorModel <- mxModel("One Factor",
type="RAM",
manifestVars=manifests,
latentVars=latents,
mxPath(from=latents, to=manifests),
mxPath(from=manifests, arrows=2),
mxPath(from=latents, arrows=2, free=FALSE, values=1.0),
mxData(observed=cov(demoOneFactor), type="cov",
numObs=500),
# add confidence intervals for free params in A and S matrices
mxCI(c('A', 'S')))
factorRun <- mxRun(factorModel)
factorCI <- omxParallelCI(factorRun) # Run CIs in parallel