umxACE, same/different sex twins

Hi

The model you wish to fit is best described as a mixture distribution, following Neale (2003). There are two scripts in the repository that may help, Acemix.R is one, Acemix2.R is the other. In your case, there is no need for the DZ parts of the script, you simply mark the probability of being MZ as (1-(2*NdzosPairs/Ntotalpairs)).

Unfortunately, these are univariate scripts, and worse they are set up in a Cholesky style. I do not recommend the Cholesky approach in general, per Verhulst et al 2019. However, it would not be so difficult to modify it to use the direct symmetric approach. Get rid of the A C and E algebras and make the X Y and Z matrices symmetric, and rename them as A C and E.

mxMatrix("Full", nrow=1, ncol=1, free=TRUE, values=.6, lbound=.01 , label="a", name="X"),
mxMatrix("Full", nrow=1, ncol=1, free=TRUE, values=.6, lbound=.01 , label="c", name="Y"),
mxMatrix("Full", nrow=1, ncol=1, free=TRUE, values=.6, lbound=.1, ubound=10, label="e", name="Z"),
    # Matrixes A, C, and E to compute A, C, and E variance components
    mxAlgebra(X * t(X), name="A"),
    mxAlgebra(Y * t(Y), name="C"),
    mxAlgebra(Z * t(Z), name="E"),  

Becomes

mxMatrix("Symm", nrow=nvar, ncol=nvar, free=TRUE, values=.6, name="A"),
mxMatrix("Symm", nrow=nvar, ncol=nvar, free=TRUE, values=.6, name="C"),
mxMatrix("Symm", nrow=nvar, ncol=nvar, free=TRUE, values=.6, name="E"),

And you would set the number of variables earlier in the script before the model definition with e.g., nvar<-5

HTH!