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library(OpenMx)
uMod <- mxModel(
"upper", type="RAM",
latentVars = c("eta"),
mxData(type="raw", observed=data.frame(id=1L), primaryKey = 'id'),
mxPath('eta', arrows=2, values=1))
for (numLower in 2:10) {
lMod <- mxModel(
"lower", type="RAM", uMod,
manifestVars = 'y1',
mxData(type="raw", observed=data.frame(y1=rnorm(numLower), id=1L)),
mxPath('one', 'y1'),
mxPath('y1', arrows=2, values=1),
mxPath('upper.eta', 'y1', values=.1, joinKey='id'),
mxComputeSequence(list(
mxComputeOnce('fitfunction', 'fit'),
mxComputeReportExpectation())))
lMod$expectation$.maxDebugGroups <- 10L
lMod <- mxRun(lMod, silent=TRUE)
target <- cbind(matrix(1, numLower, 1), contr.helmert(numLower)[numLower:1,(numLower-1):1])
rot <- -qr.Q(qr(target))
ed <- lMod$expectation$debug
# Only the sign of the first term matters.
omxCheckCloseEnough(abs(c(lMod$data$observed$y1 %*% rot)),
abs(c(ed$g2$dataVec, ed$g1$dataVec)), 1e-6)
}
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