R Functions and User Interface

folks,
short and sweet: how can OpenMx access user-written functions and functions from other packages? e.g., i would like to access alpha and sumx in the following code:

alpha <- .3
sumx <- function (x) {
sum(x)
}
x <- c(1, 2, 3)
testModel <- mxModel("testModel", mxAlgebra(expression="alpha * sumx(x)", name="test"))
mxRun(testModel)

Example:

Running modelThreshReparam3
Error: The expected covariance matrix associated with the FIML objective in model 'modelThreshReparam3' is not of the same length as the dimnames provided by the objective function.

This should read:

Running modelThreshReparam3
Error: The expected covariance matrix associated with the FIML objective in model 'modelThreshReparam3' is not of the same length as the dimnames provided by the objective function.
The expected covariance matrix is of dimension 4x4, but the length of the dimnames in the objective function is 3

Is there a function to output an mxModel to a file? I was running a simulation, and rather than extracting a few specific elements, I wanted to save the results from each model fit to a file. I tried dput(). While a file was written, I can not retrieve it using dget(). My ideal would be to be able to save the entirety of mxModel for future reference. Ideas?

topic for mxFactor

I'm trying to run a model where I need to round a value in an mxMatrix to an integer. I'm doing this in an mxAlgebra. In the help files for mxAlgebra, I noticed that there is no 'round' function listed. (There are lots of other functions: min, max, abs, sum, etc.) Is there a reason for its exclusion, or was it just forgotten?

In R, if you type ?Arith to get the help page for the S4 generic mathematical operators. An mxAlgebra should probably be able to handle all of these, and already does handle most of them.

I wonder if others would like the confidence intervals report to include the initial value in the middle as a convenience
i.e.,
confidence intervals:

                lbound        estimate        ubound
top.a[1,1]   0.6275213     0.713             0.7931507

rather than
                lbound    ubound
top.a[1,1]   0.6275213  0.7931507

Hi all,

I'm writing a simple latent change score demo using mxPath, and found something interesting. I believe we've talked about default means models before, but I don't recall.

When seeking to optimize mxAlgebra, would there be a speed benefit (or cost?) to saying instead of, for example:

mxAlgebra(rbind (cbind(A+C+E, .5%x%A+C),
cbind(.5%x%A+C , A+C+E) ), name="DZCov")

instead saying:

mxAlgebra( A+C+E , name="ACE")
mxAlgebra( .5%x%A+C+E, name="halfACE")

mxAlgebra(rbind (cbind(ACE, hACE),
cbind(hACE, ACE) ), name="DZCov")