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When estimator is GLS (or WLS), the gradient uses (line 257 in lav_model_gradient): group.dx <- -1 * crossprod( Delta[[g]], crossprod(WLS.V, diff) )
This becomes increasingly problematic if the number of variables goes up (say, for P=200 or higher). For WLS, there is not much we can do, but for GLS, we should use the 'Omega' approach as for ML.
The text was updated successfully, but these errors were encountered:
When estimator is GLS (or WLS), the gradient uses (line 257 in lav_model_gradient):
group.dx <- -1 * crossprod( Delta[[g]], crossprod(WLS.V, diff) )
This becomes increasingly problematic if the number of variables goes up (say, for P=200 or higher). For WLS, there is not much we can do, but for GLS, we should use the 'Omega' approach as for ML.
The text was updated successfully, but these errors were encountered: