Feeding aML good starting values is crucial for fast convergence. I followed the suggestions offered by the aML manual for a while. Now I no longer need to struggle with the manual: it becomes a fun game that I am really good at.
The secret is to build up complicated models piece by piece, use estimates from the simpler models as the starting values of the more complicated ones; and use stepwise procedure to get good estimates for the intercepts, then fixed effects, then random effects.
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