# Random coefficients logit estimation with Hierarchical Bayes in R

I am trying to estimate a Random Coefficients Logit model using the RSGHB R package. Thought, I came across with 2 main issues:

1. Why the gDist does not identify a non-normal distribution? No matter what vector I set for gDist the model keeps considering normal distribution for the coefficient. Also, suppose we solve that problem, which of the results are the transformed sample-level mean estimates (mean and st.dev)? There is only the C matrix which contains the individual-level estimates.

2. As regards the convergence, when can we be positive that the it has been achieved? Moreover, I have a fixed coefficient for ASC which seems not to converge, while other random coefficients do. Also, the F matrix in the results show a significant number of 0 values which creates bias in the ASC mean estimate. When I change this coefficient to random it seems to converge and there are no 0 values. What could be the problem here?