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