I would like to speed up a model. I have a data frame that is not square, that I can easily represent by a list (number of columns and rows are not fixed, but decided as input)
Now, the way I am sampling
s1 ~ normal()
s2 ~ normal()
sN ~ normal()
is building a linear array and a map array where I map every element with a parameter (it could be an vector of size N)
This is really slow because is not vectorized. Is there a solution/trick to vectorize over columns (in my example). My understanding is that lists/tuples haven’t been implemented yet.
Thanks a lot.