Today, I felt like fixing all my free parameters and call mxRun() on my model. I expected the optimizer to converge instantly or rather not to be invoked. Instead, it seems the backend is running into an infinite loop somehow. Maybe the backend needs to check the condition of no free parameters in the model.
I did this (admitted, a rather strange setting) because I intended to evaluate the -2LL of dataset "A" on a model that I ran previously on dataset "B". I thought if I fixed all parameters, set the dataset to "A" and mxRun() it, I'd get the desired -2LL of "A" under the model estimated by "B" as a result. So, I wonder what you suggest as the standard way to obtain a likelihood of a different dataset given an estimated model.