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level 1 warning as first step toward more in-depth search

Submitted by tbates on

https://github.com/OpenMx/OpenMx/blob/master/R/MxModelFunctions.R#L127-L137
Add test script checking returning first row behavior?
What is proper behavior for this?
What is the value of submodel.likelihood + submodel. A[1,1] when submodel.A is “data.X”?
It depends on how many rows in are data. If nrow(data) == 1 then data.X is the data in the first row. If nrow(data) > 1 then data.X is set to NaN. (initial compute)
NaN is dangerous because OpenMx matrix algebras are NA/NaN unsafe.

Concerning the Currently Available Versions of OpenMx

Submitted by AdminRobK on

We, the OpenMx Development Team, have heard from several of our users who have expressed confusion about which OpenMx version is the current stable release. As of 8 Jun 2014, it is version 2.2.4. We are using this announcement to resolve the confusion, explain the current situation, provide guidance for our users, and -- perhaps most importantly -- to apologize for any confusion or inconvenience we may have caused.

mxEval with Run State Space Model

Submitted by mhunter on

Charles Driver found this odd behavior: http://openmx.psyc.virginia.edu/thread/3948

On a state space expectation model that has been run, mxEval does not correctly find/use at least some definition variables.


require(OpenMx)

data(demoOneFactor)
nvar <- ncol(demoOneFactor)
varnames <- colnames(demoOneFactor)
demoOneFactorInputs <- cbind(demoOneFactor, V1=rnorm(nrow(demoOneFactor)))
ssModel <- mxModel(model="State Space Inputs Manual Example",
mxMatrix("Full", 1, 1, TRUE, .3, name="A"),
mxMatrix("Full", 1, 1, TRUE, values=1, name="B"),

mxRefModels does not work with inherited data

Submitted by mhunter on

OpenMx models support inheriting data from a parent, but the mxRefModels function chokes on this.


require(OpenMx)

data(demoOneFactor)
latents = c("G")
manifests = names(demoOneFactor)

m1 <- mxModel("model1", type = "RAM",
manifestVars = manifests, latentVars = latents,
mxPath(from = latents, to = manifests),
mxPath(from = manifests, arrows = 2),
mxPath(from = latents, arrows = 2, free = F, values = 1.0)
)
m2 <- mxModel("model2", type = "RAM",
manifestVars = manifests, latentVars = latents,

error msg: typecheck incoming covCols covRows to verifyMvnNames (file MxExpectationNormal.R)

Submitted by tbates on

in file MxExpectationNormal.R
verifyMvnNames()
attempts this:

(length(covRows) != length(covCols)) || !all(covRows == covCols))

covRows gets covDimnames[[1]]
covDimnames gets dimnames(covariance)
and covariance is flatModel[[covName]]

so the problem was embedded in an incoming flatModel (exerpted snippet below).

I am guessing that we are letting people set dimnames incorrectly outside the this code...


verifyMvnNames <- function(covName, meansName, type, flatModel, modelname, expectationName) {
covariance <- flatModel[[covName]]

tell people what is actually happening

Submitted by tbates on

re user issue http://openmx.psyc.virginia.edu/thread/1111

As Mikee N says,

if(fit function < definite & evaluations <3 & free parameters > 0){
message("your starting values are too far off reality for me find my way home...
You might try setting the means to their actual values (that often flumoxes me), and perhaps get the covariances closer to realistic values for me, but certainly start by setting each variable's mean to its actual value to give me a hint..."
}

re mxTryHard()

Would it be wise to set scale to .05 by default?

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