A graphical user interface to OpenMx
Max Weber, Slide Lecture at the Metropolitan Museum
Weird constraint problem in OpenMx
click here to download the relevant R objects
- ran three models: the first a "general model", the second and third models constrained a (1 x 4) vector of means for one group to equal the (1 x 4) vector of means for another group. the second model did this using an MxAlgebra object while the third used an MxConstraint object.
- all models converged with an NPSOL inform value of 0.
- gradient and hessian were perfectly fine for models 1 and 2 but not for model 3. largest gradient element was -40 and the norm of the gradient was 5900. the search direction at convergence (inverse(hess) %*% gradient) gave very large elements. the calculated hessian was a (1 x 1) matrix with element NA.
- yet, the second and third models gave the same function value and the same parameter estimates.
- suspect something funky with the gradient and/or hessian returned with the third model.