OpenMx (version 2.6.9)

omxParallelCI: omxParallelCI

Description

Create parallel models for parallel confidence intervals

Usage

omxParallelCI(model, run = TRUE)

Arguments

model

an MxModel with confidence intervals in it

run

whether to run the model or just return the parallelized interval models

Value

an MxModel object

Examples

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